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Liudvika Leišytė

With the increasing policy push for the contribution of universities to the knowledge economies and the industry pull for early-stage high-risk endeavors to be outsourced, university spin-off companies have increasingly drawn scholarly attention within the field of entrepreneurship. Literature distinguishes between soft channels of knowledge transfer, such as, consultancy, industry training and the production of highly qualified graduates, and hard channels such as patenting, licensing and spin-off creation (Perkmann and Walsh, 2007). Spin-off creation as a form of knowledge commercialization has drawn a great deal of attention in the literature to date as spin-off firms are tangible and observable (Zomer, 2011). Even though the literature starting in the 1980s was scarce, it has experienced an exponential increase in studies across the globe on the processes and the economic performance of university spin-offs since late 2010 (Miranda et al., 2018). Spin-offs are defined in various ways in the literature with the main commonality, that is, these are new ventures created within the auspices of research organizations (such as universities). They are founded by academics based on the technology (usually patented intellectual property) originating from research within departments, laboratories or chairs at universities. Miranda et al. (2018: 1008) see spin-off creation as a ‘process by which a company is created from another pre-existing entity’ and its main purpose is to exploit the processes, services and products developed based on the knowledge created at a university’.

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Liudvika Leišytė

Gender inequalities in science persist across the EU member states with the underrepresentation of women in the top echelons of scientific hierarchies. In the past two decades, the European Union tried to address this issue with a mix of policies based on social and economic rationales. The chapter identifies three policy challenges that still persist today: the underrepresentation of women in top positions in science and in decision-making bodies, the gender pay gap, and the absence of gender in research content. The analysis shows that the complexities of actors and the importance of institutional entrepreneurs, networks and advocacy groups have led to a more non-linear policy learning from ‘fixing the women’ to ‘fixing the institutions’ approaches. The chapter points out how the economic rationale has increasingly taken over the social equality rationale regarding gender in research policies. The increased rationalization of research organizations allows the implementation of gender policies, although a lot of implementation stays at the ideational level.