The paper presents results from social network analysis applied to data on\ud
patenting of academics inventors employed in two Italian universities (Trieste University\ud
and Udine university, both located in Friuli Venezia Giulia region). The aim is to compare\ud
the co-invention networks generated by the academic inventors, tenured by one of the two\ud
universities, in their patenting activity with several organisations—firms, public research\ud
organisations—and in their activity for patents owned by one of the two universities.\ud
Results show that, despite the structural similarity, non-marginal differences emerge in the\ud
interaction of the two forms of patenting across the two universities. Empirical evidence\ud
suggests new research questions related in particular to the role played by the differing\ud
university patenting strategies in shaping local network
The role of academics in patenting activity is not limited to patents owned by universities (universityowned patents) as academics often contribute to inventions patented by other organizations (university-invented patents). Moreover, it has been shown that academics play central roles inside the patenting network and that appropriability rules can interfere with the pattern of knowledge diffusion. In this study, we use social network analysis to analyze university-owned and university-invented patents in two Italian universities. We investigate the quality of the ties and the reasons why academics patent with their universities or with external organizations. We identify three subnetwork typologies. Two out of three subnetworks well exemplify the conditions for university ownership and for professor privilege, but the most complex structure, stemming from academic gatekeepers, need more flexible property attribution arrangements. In this contexts, aggressive policies toward university ownership can damage the networks with the highest grade of science-industry cross-fertilisation.
The idea that wages are determined by firm and individual characteristics suggests that there is a firm effect that influences wage differentials. This paper presents the results of an empirical analysis of gender wage differentialsbased on INPS data for people between the ages of 20 and 25 employed in the private sector in 1996 -which takes into account the characteristics of workers and firms using a two-level random-effects model. Firm variables proved to be significant, and the proportion of females in the firm showed a negative effect on the wages of both men and women.
In this paper, we present the results of a network analysis applied to academic patent data in a subsector of the chemical field in Italy in the period 2000–2011. In particular, we analyse the micro-level interactions to point out the different network structures shaped by university-owned and university-invented patents. We detected three subnetwork typologies (labelled type A, B, and C) that exemplify different qualitative relational structures as well as different attributions to propriety rights. Type A (open science) exemplifies the typical owned patent; type B (multiple ties) represents the hybrid structure with multiple ties and involvement of academics as individuals and of universities as organisation; type C (disconnected subnetworks) represents the typical invented patent with no role of universities as organisation. The whole network seems to show a breaking point in terms of connectivity around 2005, a year that marks a change in policy rule and strategic orientation of Italian universities towards patenting. After 2005, the number of actors grew disproportionally and the network appears disconnected in several comparable components. Also, the composition in terms of subnetwork types changed. The overall picture seems to underline a big structural change dominated by the important increase of academic patenting both direct (university ownership) and indirect (increasing academic patenting)
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