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Personal ties in university-industry linkages: a case-study from Argentina

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Abstract

Many previous studies have advanced in identifying different modes of interactions between public research organizations (PROs) and industry and in assessing their associated benefits. However, few studies have adopted a social network perspective to analyze the relation between the characteristics of social ties and actors and specific aspects of PROs-industry interactions. Based on case-study evidence of linkages formed by researchers from a medium-sized Argentinian university, we include the strength of tie as one of the driving factors in the selection of PROs-industry channels. Following Granovetter (Am J Sociol, 1360–1380, 1973) we assess the concept of strength of tie as a linear combination of friendship, trustworthiness, reciprocity of knowledge exchange, and frequency of interaction. Using econometric techniques we find that stronger ties motivate the selection of longer-term bi-directional modes of interactions which, in turn, create knowledge benefits for PROs. In contrast, weaker ties are good enough for service provision, which creates financial benefits for PROs. These findings bring to the fore the need to conceptualize PROs-industry collaborations holistically, including the relational, social and historical nature of these processes side by side with technical and legal processes.

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Fig. 1

Sources: Muñoz et al. (1999), Kababe Y. (2010) and Ministry of Science, Technology and Innovation. Argentina. (2015)

Fig. 2

Source: Ministry of Science, Technology and Innovation. Argentina

Fig. 3

Source: Ministry of Science, Technology and Innovation. Argentina

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Notes

  1. Varsavsky (1973), proposed what López (2007) called a linear model but “the other way around”. He argued that society had to set the productive priorities from which technological needs were to be derived. Those needs should be satisfied by the S&T complex. In turn, Sábato and Botana (1968) developed the triangle model to emphasize the need for public policies to integrate the three vertexes: state, productive sector and scientific sector. Sábato’s ideas set a precedent for the “triple helix” model of Etzkowitz and Leydesdorff (1997).

  2. In opposition to previous ideas, international knowledge was viewed as an opportunity for development. In fact, the 1990s marked a period of liberalization policies in Argentina. It was believed that trade liberalization would promote technological innovation due to the increase in foreign competition and the reduction in price of imported capital goods. Policies during this period also relied on foreign direct investment as a mechanism for successful technology transfer from abroad.

  3. See National Bicentenary Strategic Plan of Science, Technology and Innovation (2006–2010) and Argentina Innova 2020: National Plan for Science, Technology and Innovation. Strategic Guidelines 2012–2015.

  4. The content of these regulations was authorized by Article 19 of Law 25,467 (2001) but they were only enacted in 2009.

  5. See Arza and Vazquez (2010), for the Argentinian study, Fernandes et al. (2010), for Brazil, Orozco and Ruiz (2010), for Costa Rica, and Dutrénit et al. (2010), for the Mexican case study.

  6. In a recent paper, Kruss (2012) used the same taxonomy to relate channel with benefits and also with risk of interactions for the biotechnology sector in South Africa.

  7. These hypotheses have been empirically tested in other case studies (see Arza and Vazquez 2010, 2012; Dutrénit and Arza 2010; Dutrénit et al. 2010; Fernandes et al. 2010; Orozco and Ruiz 2010).

  8. We originally estimated a multinomial logit since our dependent variable was actually polytomous (there were four categories for the variable channel of interaction) and we were interested in analyzing whether the strength of ties inclines researchers and firms towards one or another channel of interactions. However, since there were too few observations in two of the four categories, we were forced to interpret our results for just one pair of relative probabilities (i.e. that which relates bi-directional with service channels.) Results were perfectly consistent with those found when estimating dichotomous probability models, which therefore are the ones we decided to report.

  9. The researchers we interviewed came from five different schools: economics (3 researchers), exact science which includes information technologies (ICT) & physics (17), agronomy (20), veterinary (34), and engineering (52). We include a dummy for each with the latter being the base category. Since there were too few researchers from the school of economics we had to drop that category (i.e. researchers from that school were then by the default included as part of the base category).

  10. Independent variables from Eqs. (1) and (2) were used as instruments robust cluster standard errors.

  11. In research teams of more than ten members, there is in average one Ph.D. student per full-time researcher, while in research teams of less than ten members, the proportion is one Ph.D. student every two full-time researchers.

  12. Only 17% of ICT interactions are carried out in the bi-directional channel, while 66% of physics interactions use that channel.

  13. In “Appendix 2” we presented the results of the first stage for IV 2SLS estimation and also the estimated coefficients for Eq. (1) for 3SLS estimation. These results are very similar to those presented in Table 4.

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Acknowledgement

We would like to thank very useful comments of two anonymous referees. National Research Council of Argentina (CONICET), Center National University (UNICEN) and PIP 0268/2012 CONICET contributed funding for this project. Also, we would like to thank the researchers who agreed to participate in the interviews and answered our questions.

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Authors and Affiliations

  1. National Scientific and Technical Research Council—(CONICET) Argentina and Research Centre for Transformation (CENIT) associated to Tres de Febrero University (UNTREF), Callao 353, 3 B, CP 1022, Buenos Aires, Argentina

    Valeria Arza

  2. Management Studies Centre (CEA), National University of Central Buenos Aires (UNICEN), Pinto 399, Tandil, Buenos Aires, Argentina

    Mariela Carattoli

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  1. Valeria Arza
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Correspondence to Valeria Arza.

Appendices

Appendix 1

See Table 6.

Table 6 Description of variables
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Appendix 2

See Table 7.

Table 7 Probability estimates of choosing bi-directional and service channel when estimating the benefits of interaction
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Arza, V., Carattoli, M. Personal ties in university-industry linkages: a case-study from Argentina. J Technol Transf 42, 814–840 (2017). https://doi.org/10.1007/s10961-016-9544-x

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