Interactions between public research organisations and industry in Argentina

Arza, Valeria; Vázquez, Claudia Mónica

doi:10.3152/030234210x512728

Cited by 47 publications

(40 citation statements)

References 18 publications

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“…Our results also show that researchers in certain knowledge areas, such as Biology & Chemistry and Engineering, tend to collaborate much more than those from Medicine & Health Sciences. These results seem to complement those found by Dutrénit, et al (2010a) and Arza and Vazquez (2010), as, according to their findings, researchers from Biotechnology & Agronomy tend to connect more than those in Physics & Mathematics. The latter is in line with the ideas of the Pasteur quadrant proposed by Stokes (1997).…”

Section: Firmscontrasting

confidence: 53%

“…Other Latin-American countries report some analogous results based on the same analytical framework. Arza and Vazquez (2010) found that bi-directional and the service channels bring intellectual benefits, and service channel yield economic benefits in the case of Argentinean researchers; traditional and bi-directional channels yield production and innovation benefits to Argentinean firms. Fernandes, et al (2010) found that bi-directional, traditional, and service channels contribute to both intellectual and traditional benefits for university researchers, as well as to production benefits for firms, while bi-directional and traditional channels are relevant to innovation benefits.…”

Section: Stage 2: Which Are the Main Types Of Knowledge Transfered Thmentioning

confidence: 99%

“…Institutional factors include institutional affiliation (researchers working in centers have more opportunities to connect than those working in universities (Boardman and Ponomariov, 2009)), the mission of the university (universities that emphasize entrepreneurship tend to collaborate more with firms than those that do not (Etzkowitz and Leydesdorff, 2000;Mowery and Sampat, 2005;Jain, et al, 2009)), previous experience in technology-transfer (D'Este and Patel, 2007), the scale of research resources and access to different sources of funding for research by the various departments (Lee, 1996;Schartinger, et al, 2002;Colyvas, et al, 2002;Bozeman and Gaughan, 2007), and the quality of research (Mansfield and Lee, 1996;Schartinger, et al, 2002). Individual factors include the gender and age of faculty members (Jensen, et al, 2008;Giuliani, et al, 2010;Arza and Vazquez, 2010;Wigren et al, 2011), previous experience in interaction (Bekkers and Bodas Freitas, 2010), the academic status of faculty members and their research fields (Friedman and Silverman, 2003;Bercovitz and Feldman, 2003;D'Este and Patel, 2007;Bekkers and Bodas Freitas, 2008;Jensen, et al, 2008;Boardman and Ponomariov, 2009;Rivera, et al, 2011;Wigren, 2011), the extent of academic collaboration (Boardman and Ponomariov, 2009;Dutrénit, et al, 2010a;Rivera, et al, 2011), faculty members' motivation (Jain, et al, 2009), and the faculty members' centrality in the network (Giuliani, et al, 2010).…”

Section: Stage 1: Why Do Pro and Firms Engage In Collaboration? The Dmentioning

confidence: 99%

“…The authors focus either on PRO (e.g., Melin, 2000;Bozeman and Corley, 2004;Eun, et al 2006;D'Este and Patel, 2007;Boardman and Ponomariov, 2009;Göransson, et al 2009;D'Este and Perkmann, 2010;Wigren et al, 2011) or on the perspective of firms (e.g., Laursen and Salter, 2004;Hanel and St-Pierre, 2006;Fontana, et al, 2006;Mathews and Mei-Chih, 2007;Jensen et al 2007;Ayadi, et al, 2009); still other studies have analysed PRO-I interactions from both perspectives (Carayol, 2004;Bekkers and Bodas Freitas, 2008;Intarakumnerd and Schiller, 2009;Dutrénit, et al, 2010;Arza and Vazquez, 2010;Fernandes, et al, 2010;Orozco and Ruíz, 2010). Three stages of the linking process can be identified: drivers of interaction, channels of interaction, and the perceived benefits.…”

Section: Introductionmentioning

confidence: 99%

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Best channels of academia–industry interaction for long-term benefit

2012

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Interactions between public research organizations and industry can be conceptualized as having three main stages: drivers of interaction, channels of interaction, and the perceived benefits from collaboration. Both of the agents differ in terms of the incentives they have to collaborate and the behaviors they adopt during the collaboration process. Following a three-stage model based on Crépon, Duguet, and Mairesse (1998), this paper discusses the impact of drivers of collaboration on channels of interaction, and the impact of these channels on the perceived benefits by researchers and firms. The methodology also allows firm-level benefits from interaction to be connected with researchers' characteristics via the analysis of four common channels of interaction for firms and researchers. The study is based on original data collected through two surveys, carried out in Mexico during 2008, of R&D and product-development managers of firms and of academic researchers. Our results show that all channels of interaction play an important role in determining benefits; however, they differ in terms of their impact on short-or long-term benefits for firms. The channels related to joint and contract R&D, property rights, and human resources are the best, as they have a higher impact on long-term benefits for firms. Policy implications derived from this study focus on specific actions that enhance those researchers' characteristics related to the best channels for fostering long-term benefits for firms.

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Section: Firmscontrasting

confidence: 53%

Section: Stage 2: Which Are the Main Types Of Knowledge Transfered Thmentioning

confidence: 99%

Section: Stage 1: Why Do Pro and Firms Engage In Collaboration? The Dmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Best channels of academia–industry interaction for long-term benefit

2012

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“…There have been many case studies at national or regional level investigating collaboration involving these three spheres (e.g. Boardman 2009;Inzelt 2004Inzelt , 2010Geuna and Rossi 2011;Arza and Vazquez 2010;Chataway and Hewitt 1999;Dutrenit and Arza 2010;Liang et al 2012;Sutz 2000) which identified many characteristics and institutional settings in which these relationships are evident. Perkmann et al (2013) provides a review of the literature on university-industry relations.…”

Section: Literature Contextmentioning

confidence: 99%

Re-aligning the Triple Helix in post-Soviet Armenia

Inzelt

2015

Triple Helix

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In the age of Open Innovation, it is vital for a country in the lower middle-income bracket to free itself from those constraints which seriously weaken the links between science and industry. A descriptive analysis of these linkages in a post-Soviet economy-Armenia-sheds some light on developments in policy-making which reinforce the interests of the private sector in the academic research and development (R&D) sphere. However, the way of thinking is still predominantly the 'science-push' model-which is far removed from the (horizontal) Triple Helix concept. According to empirical analysis, the scarcity of innovative companies is a serious handicap for industry-science collaboration and if the private sector has little demand for knowledge or science, then the innovation system cannot be effective. Very few higher education institutions (HEIs) or research institutes have devoted attention to the management of technology transfer, including necessary human resources. Human capacity problems, outdated infrastructure and an ageing workforce are significant barriers in scientific organisations. The autonomy of scientific organisations is an important asset which only half-exists in Armenia. On the escape route from a command economy, there are two potential traps on the way of autonomy: one occurs when the state overarches legal autonomy and creates a semi-autonomous situation; the other arises when the state is reluctant to regulate the framework for autonomous scientific organisations. Both exist in Armenia. Inzelt Triple Helix (2015) 2:15 DOI 10.1186/s40604-015-0025-2 French: Réajuster la Triple Hélice à l'Arménie post-soviétique Résumé: A l'âge de l'innovation ouverte, il est vital pour un pays se situant dans la fourchette des bas-moyens revenus de se libérer des contraintes qui affaiblissent sérieusement les liens entre science et industrie. Une analyse descriptive de ces liens dans une économie post-soviétique, -l'Arménie -, donne un éclairage sur l'élaboration des politiques qui renforcent les intérêts du secteur privé dans la sphère académique de R&D. Cependant, le mode de pensée prédominant reste le modèle d'innovation induit par la science, -qui est très éloigné du concept (horizontal) de Triple Hélice. Selon les analyses empiriques, la rareté de compagnies innovantes est un handicap sérieux pour la collaboration entre science et industrie, et, si le secteur privé a peu de demandes en termes de connaissance ou de science, alors le système d'innovation ne peut pas être efficace. Très peu d'institutions d'enseignement supérieur (IES) ou d'institutions de recherche ont prêté attention à la question de la gestion du transfert de technologie, y compris aux ressources humaines nécessaires. Les problèmes liés aux moyens humains, à l'infrastructure obsolète ou à une force de travail vieillissante sont des obstacles de taille pour les organisations scientifiques. L'autonomie des organisations scientifiques est un atout important pourtant quasiinexistant en Arménie. Pour sortir d'une économie planifiée, il...

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