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on Knowledge Management and Knowledge Economy |
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Issue of 2011‒08‒15
three papers chosen by Laura Stefanescu European Research Centre of Managerial Studies in Business Administration |
| By: | Marina van Geenhuizen (Delft University of Technology, Delft); Peter Nijkamp (VU University Amsterdam) |
| Abstract: | Smart high-tech companies are characterized by knowledge intensity and open innovation. Even when these companies emerge in spatial clusters or dense urban places, they may utilize knowledge networks on a global scale. However, there is not much insight into the factors that shape knowledge networks, the role of virtualization herein and the impact of on global knowledge sourcing on local connectedness. This paper seeks to fill these gaps in understanding, by drawing on a selected sample of young high-technology companies in the Netherlands and application of rough set analysis to identify homogeneous categories of companies in the highly differentiated segment of young high-tech companies. The outcomes suggest that employing mainly local and employing mainly global knowledge networks coexist in city-regions, and that only part of the globalized companies are losing local connectedness, particularly those involved in co-creation with global customers and those acting as learning partners of multinational corporations ('reverse' knowledge transfer). Factors counteracting a weakening of local connectedness are specific local knowledge relationships and the strategy of developing local/regional customer markets. |
| Keywords: | high-technology companies; open innovation; knowledge networks; strategic focus; dynamic capabilities; virtualization; local connectedness; rough set analysis |
| JEL: | D21 |
| Date: | 2011–08–09 |
| URL: | http://d.repec.org/n?u=RePEc:dgr:uvatin:20110119&r=knm |
| By: | Andrea Caragliu (Politecnico di Milano); Peter Nijkamp (VU University Amsterdam) |
| Abstract: | Knowledge triggers regional growth. Evidence suggests that skilled labour force concentrates in islands of innovation, determining an advantage for innovative regions and a challenge for lagging ones. We address the role of knowledge in shaping effective markets for skilled labour. Estimates are based on the Lucas (1988) model, with EVS and EUROSTAT data. The externality driving growth in the model is cognitive capital. Empirical tests show that a higher endowment of cognitive capital generates increasing returns to knowledge, favouring the emergence of islands of innovation; regions with a high endowment of cognitive capital attract knowledge spillovers from neighbours. |
| Keywords: | human capital; cognitive capital; knowledge spillovers; islands of innovation |
| JEL: | C21 E24 R11 |
| Date: | 2011–08–09 |
| URL: | http://d.repec.org/n?u=RePEc:dgr:uvatin:20110116&r=knm |
| By: | Cerulli Giovanni (Ceris - Institute for Economic Research on Firms and Growth, Rome, Italy) |
| Abstract: | The aim of this paper is twofold: on one hand, from a methodological-statistical perspective, it develops a responsiveness-based index for a series of input factors on a specific target variable (assumed to capture the phenomenon the analyst wishes to look at), by means of an extended version of a random coefficient regression approach; on the other hand, it applies this methodology to the case of countries’ innovation performance, where the target variable is the country number of patents (as proxy of “innovativeness”), and where inputs are chosen according to the literature dealing with the measurement of country technological capabilities. The novelty of the approach presented in the paper regards the possibility of extracting from data a country-specific “reactivity effect” or “responsiveness” (that is, mathematically, a derivative) to each single input feeding into the regression. Thus, the paper provides a promising approach for ranking countries according to their responsiveness to specific inputs, an approach that can be complementary to the analysis on “level” performed, for instance, in the canonical composite indicators’ literature. As for results on countries’ innovation function, besides a (new) ranking of countries, this approach allows also for testing - in an original and straightforward way - the (possible) presence of increasing (decreasing) returns. Two years are considered and compared, 1995 and 2007, on 42 countries. Our tests conclude that in both years innovative increasing returns are at work, although in 2007 their strength drops considerably compared to 1995. According to a huge literature on the subject (both neoclassical and evolutionary), we conclude that a self-reinforcing mechanism in new knowledge production, absorption and diffusion is at the basis of these results. As for the structural change found between 1995 and 2007, we deem it to depend on the growing globalization of production and innovation processes and on the brilliant growth of some developing countries worldwide, with a remarkable role played – according to our results – by post-communist economies. |
| Keywords: | Responsiveness, Country indicators, Random coefficient regression, Innovation function |
| JEL: | C21 O31 Q01 |
| Date: | 2010–12 |
| URL: | http://d.repec.org/n?u=RePEc:csc:cerisp:201010&r=knm |