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The governance of universities and the establishment of academic spin-offs

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Abstract

While the metaphor of entrepreneurial ecosystem has become popular in academia, industry and government, one aspect is almost neglected, the role of universities. In particular, there is a paucity of studies that examine the governance of universities in relation to their engagement within the ecosystem. This paper relates for the first time the governance structure of universities to their capacity to foster the establishment of academic spin-offs. Thanks to a regulatory change imposing to Italian State universities the enrollment of lay members (i.e., external directors) in their board of directors, we can observe their appointment as an exogenous shock. We find that, while half of the universities appoint the minimum required number of lay members, others appoint more, up to creating board of directors where only the rector is not external. Moreover, there is a strong variety in the type of experiential capital that these lay members bring to universities. While some are entrepreneurs or managers of private firms, others are local stakeholders, such as lawyers or members of foundations or chambers of commerce. Such variance is reflected in the stimulus they exert on the creation of spin-offs. Using a regression discontinuity design on a sample of 1234 spin-offs from 66 universities, our longitudinal study of 1122 university-year observations shows that the rate of establishment of technology spin-offs increases more when more entrepreneurs are appointed. Local stakeholders in the university’s board of directors, by contrast, are associated with increased establishments of service-oriented spin-offs.

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Notes

  1. The chairman of the board is always the rector of the university and the academic senate is anyway composed by faculty and administrative staff members. Student representatives must be elected in both the academic senate and in the board of directors. We focus on the board of directors as academic senates have lost authority relative to boards (Capano et al. 2016; Donina et al. 2015a).

  2. The Law 240/2010 only applies to the 66 Italian state universities, while the 28 non-state universities (private or run by other public entities) are not involved. A comparison of the effect of reform on the 28 non-state universities, therefore, does not apply. Further, we ruled out the hypothesis to use them as a matching sample, because the governance framework largely differs from that of state universities (Capano et al. 2016).

  3. At the time of the governance survey, two institutions did not participate, while four were in the process to select their board members. For these institutions, data have been collected directly from the institutions.

  4. The database is available at www.spinoffricerca.it.

  5. The percentage of technology-based spin-off in our sample is higher than in Meoli and Vismara (2016) due to our selection of state universities, which spin out a smaller number of non-technology spin-offs.

  6. The rector is a member of the board according to the law, as well as representatives of students, in a ratio of at least 15%. Given that these components are necessary, the calculation of the lay representativeness was performed excluding them.

  7. A third order polynomial is included in all the regression analysis of the paper. Robustness analyses with first- and second-order formulations have been running, yielding qualitatively the same results. The use of higher order polynomial is indeed discouraged by recent literature (Gelman and Imbens 2014).

  8. In our regression analyses, the presence of lay members is measured either through the total number (Lay members in the board) or the percentage (Lay presence in the board) of lay members in the board; Entrepreneurs and Local Stakeholders are measured through the number of members in either category in the board (Entrepreneurs in the board, and Local stakeholders in the board). Notice that these variables do not need to be interacted with the forcing variable (Law 240), as in a traditional RDD framework, given that their value is 0 before the reform.

  9. The Herfindahl–Hirschman Index, or HHI, is used in economics and business studies as a measure of concentration widely applied in competition law, antitrust and also technology management. It is defined as the sum of the squares of each share of the firms within the industry where the market shares are expressed as fractions. In our paper, the shares represent the disciplinary representation in each university. In this study, we use the Italian classification of university degrees into 14 disciplinary fields. The result can range from 0 to 1, identifying in the former case a university offering all type of disciplinary fields, and in the latter an institution focused on a single discipline. It is therefore an “inverse” measure of complexity, as 0 identifies the maximum, and 1 the minimum, level of complexity.

  10. This ratio identifies how strongly the institutional resources depend on student fees, i.e., how much the university activity needs to satisfy the market demands (Hemsley-Brown and Oplatka 2010).

  11. We refer to the Nomenclature of Territorial Units for Statistics (NUTS), a geocode standard for referencing the subdivisions of countries for statistical purposes developed by the European Union. For each EU member country, a hierarchy of three NUTS levels is established by Eurostat. Our set of dummy variables is based on the NUTS-1 coding, which identifies five macro-areas in Italy.

  12. The first-stage regressions show that all instruments are strong, in that they significantly contribute to determine the potentially endogenous variables they are related to. In particular, the HHI (Herfindahl-Hirschman index) calculated with respect to the disciplinary fields taught by each university, as an inverse measure of internal complexity, is a negative determinant of Lay presence in the board (coefficient = − 0.230, p value < 0.05) and Lay members in the board (coefficient = − 1.446, p value < 0.05); the ratio between total tuition fees and the resources available through the central government’s public budget is a determinant of Entrepreneurs in the board (coefficient = 2.881, p value < 0.01), and the ratio between the central government’s public budget and the number of enrolled students is a determinant of Local stakeholders in the board (coefficient = 0.272, p value < 0.01). As far as the excludability of the instruments from the outcome regressions is concerned, an empirical validation is always challenging, but we are no aware of no theoretical or empirical linkage between such variables and the creation of academic spinoffs.

  13. Sussan and Acs (2017) provide an integration of digital ecosystems and entrepreneurial ecosystems to identify digital entrepreneurial ecosystems. Their framework conceptualizes ecosystems between users and infrastructures, and between agents and institutions. At one end, there are digital marketplaces that match users and agents. Crowdfunding platforms are a prominent example (Vismara 2016, 2017). At the other ned, there are digital infrastructure and institutions to define digital infrastructure governance.

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Acknowledgements

This paper was presented at the Small Business Economics Special Issue Development Conference “The Governance of Entrepreneurial Ecosystems,” held in Catania, Italy, on September 29–30, 2016. We thank the conference participants, the guest editors Massimo G. Colombo, Giovanni B. Dagnino, Erik E. Lehmann, and Mari-Paz Salmador as well as the two anonymous reviewers for helpful comments.

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Authors and Affiliations

  1. CCSE, University of Bergamo, Bergamo, Italy

    Michele Meoli, Stefano Paleari & Silvio Vismara

  2. Department of Management, Information and Production Engineering, University of Bergamo, via Pasubio 7b, 24044, Dalmine, BG, Italy

    Michele Meoli, Stefano Paleari & Silvio Vismara

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  1. Michele Meoli
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  2. Stefano Paleari
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  3. Silvio Vismara
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Correspondence to Silvio Vismara.

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Meoli, M., Paleari, S. & Vismara, S. The governance of universities and the establishment of academic spin-offs. Small Bus Econ 52, 485–504 (2019). https://doi.org/10.1007/s11187-017-9956-5

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