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Intellectual property protection mechanisms and the characteristics of founding teams

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Abstract

Intellectual property protection mechanisms (IPPMs) are critical to fostering science, technology, and innovation, and their relevance has grown enormously with the increased trade in goods and services involving patentable technologies. Scholars have investigated factors that facilitate or hinder the use of such IP protection strategies by identifying related country, sector, and firm characteristics. However, the extant literature has overlooked the role of the characteristics of a firm’s founding team on the choice of an IPPM strategy. Using data from a large cross-sectional sample of European small, young, and innovative firms, we show that controlling for firm size, R&D intensity, and other firm and market effects, founding team characteristics, such as gender and education, greatly influence the choice of a strategy. In particular, in line with the general finding that women patent less, we find that firms with more women in the founding team patent less than firms with more male founders; but contrary to the literature that has primarily focused on large firms, we find that as the number of female founders increases, small, young entrepreneurial firms tend to use less informal IPPMs rather than formal IPPMs. We also find, within the context of entrepreneurship policy, that the education and not experience of founding team members is a main predictor of IP adoption.

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Notes

  1. An exception is the study of Gallié and Legros (2012) which relate human resources strategies to the choice of IPPM and finds that human resource management influences firms’ strategic choices and especially the choice of the means of IP protection. Indeed, employees’ job mobility affects secrecy and the incentive to innovate (Cooper, 2001), resulting in efforts to control the communication flows between workers and the external environment.

  2. Despite the label “informal,” these types of IPPMs are often sealed by legally binding contracts, such as non-disclosure agreements which serve to protect trade secrets.

  3. “Knowledge-intensive entrepreneurship concerns new ventures that introduce innovations in the economic systems and that intensively use knowledge. From this broad definition, it follows that knowledge-intensive entrepreneurship may take place in various ways: through the foundation of new firms or through the display of entrepreneurial spirit with existing firms or through the action of single individuals within non-profit organizations such as universities or public laboratories” (Malerba, 2010, p.4).

  4. A complete description of the AEGIS database is in Caloghirou et al. (2014). See also, https://cordis.europa.eu/project/id/225134/reporting. Additional information on the AEGIS database is available from the authors. The data used in this paper were graciously provided though Caloghirou.

  5. The architects of the AEGIS database realized that firms in smaller countries would need to be over sampled. To account for non-random sampling across countries, sampling weights are used in the econometric analysis below. See Caloghirou et al. (2014) and Link and Swann (2016) on this issue.

  6. The high-tech sector includes aerospace; computers and office machinery; radio-television communication equipment; manufacture of medical, precision and optional instruments; pharmaceuticals; manufacturer of electrical machinery and apparatus, manufacturer of machinery and equipment, chemical industry. The low-tech sector includes paper and printing; textile and clothing; food, beverage and tobacco; wood and furniture; basic metals; fabricated metal products. The Knowledge-intensive business services (KIBS) sector includes telecommunications; computer and related activities; research and experimental development; selected business services activities.

  7. The IPPMs reported in the AEGIS survey match those on the CIS and were used by Veugelers and Schneider (2017); however, confidentiality agreements were not on the CIS, but design and utility models were.

  8. Confidentiality agreements (or non-disclosing agreements, NDA) are legal contracts between parties that outline confidential information that the parties wish to share with one another, excluding access to the information by third parties. Trade secrets, or secrecy, are practices or business methods that are generally unknown outside the company. Lead time advantage refers to the advantage that the first mover enjoys int the marketplace. Finally, complexity of design, typically used for telecommunications and consumer electronics product, is the use of complex manufacturing techniques that sets products apart from lower-quality imitations.

  9. It is important to point out that the available evidence relies on surveys where firms are asked to report whether they have formal IPPMs such as patents or use informal types protection mechanisms like lead time. In the first case, the use of patents can be verified, whereas reporting the use of first-mover advantage may be subjective to the respondent firm.

  10. The results of t-tests with unequal sample size are not reported in Table 5, but they are discussed in the paper.

  11. The indicator of market power is based on the survey question related to the number of competitors "Right now, are there other businesses offering the same products and/or services to your potential customers?" Answers: Yes, many; only a few; no other competitors. Given that these companies are all SMEs, it is plausible to assume that if the market is populated by many competitors, they do not have the same power to determine the market price as for example Apple Inc. in the smartphone market.

  12. All the tables with estimation results report the computed marginal effects, which are to be interpreted as follows: for continuous variables an increase by 1% (or 1 unit or 10% in case of logged variables) in x corresponds to a \(\beta\) (multiplied by a 100 in case of unit change or change in logs) percentage points change in probability of choosing an IPPM; for dummy variables the marginal effect tells us that category 1 corresponds to a \(\beta *100\) change in probability of choosing an IPPM. For example, the coefficient of -0.012 for the variable "women" means that an additional woman in the founding team decrease the probability of choosing an IP strategy by 1.2 percentage points.

  13. There is a rich literature that shows that women do patent less than men. That literature was recently summarized by Link and Morrison (2019). In their literature review, they point out that the gender-patent literature has primarily focused patent searches for the first listed owner of the patent. The subsequent comparisons are between male and female scientists and make and female STEM employees. Most of the cross-sectional firm studies (e.g., Veugelers and Schneider, 2017) do not consider or do not have access to the gender of the firm owner much less to the gender of the founding team.

  14. We thank an anonymous reviewer for urging us to emphasize this point.

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Acknowledgments

The authors thank the participants to the workshop on Challenges of Innovation Policy at Universitat Rovira i Virgili (Reus), Antonio Vezzani (Roma Tre University, Italy), Mafini Dosso, Emanuele Pugliese and Fernando Hervás (JRC Seville) for their comments and suggestions on an earlier version of this paper. Any remaining shortcomings are ours alone.

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  1. Joint Research Centre, European Commission, Seville, Spain

    Sara Amoroso

  2. University of North Carolina at Greensboro, Greensboro, USA

    Albert N. Link

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Correspondence to Sara Amoroso.

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Amoroso, S., Link, A.N. Intellectual property protection mechanisms and the characteristics of founding teams. Scientometrics 126, 7329–7350 (2021). https://doi.org/10.1007/s11192-021-04098-4

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