CONICET | Buscador de Institutos y Recursos Humanos

Several contributions have showedthat different industries exhibit different characteristics in terms ofinnovation, linkages with universities and research and development (R+D)centers, and capacity for technological diffusion through their relationshipwith other industries (Freeman et al., 1982; Geroski, 1991; Nelson andWinter, 1977). Literature has resorted toconcepts as technological regimes (Malerba et al., 1997; Malerba and Orsenigo, 1997), sectoral systems of innovation (Malerba,2002), technological trajectories (Dosi 1982), or sectoral patters (Dosi, 1982; Malerba and Orsenigo, 1997; Pavitt, 1984) in order to account for such differences. Sincethen, it has been proposed several sectorial taxonomies aimed to distinguishedtechnological intensity of sectors in trade or productive specialization ofdeveloped (Archibugi and Michie, 1995; Castellacci, 2008;Hatzichronoglou, 1997; Lall et al., 2006; Marsili and Verspagen, 2002) and developing countries (Katz and Stumpo, 2001; Lall, 2001; Petralia and Marin,2015). According with this literature, there aredifferences among sectors regarding their capacity to innovate, self-transformon basis of technological change and being diffusers of innovations and newknowledge (Rosenberg,1963). Therefore, the trade andproductive specialization profile of countries can affect their dynamics ofinnovation, learning and technological change.According to a Schumpeterianperspective, economic development and structural change are processes ofqualitative transformation of a productive structure, which emanate fromintroduction of new products and processes, or, in other words, innovation andtechnological change. If sectors show differences in the way they learn, adoptand diffuse innovation, therefore, the productive and trade profile is nottrivial on their effect on potential economic development. Recently, some papers have minimizedthe relevance of sectorial differences and, although they are aware on therelationship between specialization profile and development, they also indicatethat there are successful development strategies based on sectors traditionallyclassify as low R+D intensity or low technological dynamism, like strategiesbased on natural resources (Iizuka and Katz, 2010; Pérez, 2010;Petralia and Marin, 2015; REDSUR, 2014). The main argument of this worksrelies on the fact that technology opportunities, understood as the easiness ofinnovating for any given amount of resources invested in search (Malerba andOrsenigo, 1997), and measured as the effectiveness of innovation activitiesexpenditures, are dependent of historical and productive context. Therefore, a newtechnological paradigm may offer new opportunities for traditional sectors. Forexample, new information and communication technologies or biotech industrieshas the potential to transform sectors in primary activities, like agriculture,opening them to new opportunities to innovate. In this regard, it is difficultto stablish which sectors are opener to introduce new knowledge and act asdynamic activities in technology diffusion. Nevertheless, an approachexclusively focused on opportunity may hide how other attributes oftechnological regimes interplay with opportunity and may lead to a misleadingimpression of learning processes in sector dynamics. The concept oftechnological regimes (Malerba and Orsenigo, 1997) considers, besidesopportunity, cumulativeness, appropriability and technological base. Consideringthese four attributes gives a more complex perspective of innovation, learning,and capacity building processes at sectoral level.In this paper,we propose to analyze sectorial innovation profile of manufacture industry inArgentina. We followed Malerba and Orgsenigo (1997) technological regimes. Weoperationalized and estimated different indicators for innovation efforts,appropriation strategies and learning sources. Then, we applied a multilevelmodel to evaluate the differences among sector in the association between thoseindicators and the introduction of successful innovation. This exercise allowedus to estimate sectorial indicator for opportunity, appropriability,cumulativeness (learning based on experience) and technological base (learningbased on interaction with universities or other firms).

enviar mensaje