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on Knowledge Management and Knowledge Economy |
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Issue of 2017‒01‒15
four papers chosen by Laura Ştefănescu Centrul European de Studii Manageriale în Administrarea Afacerilor |
| By: | C. Conti (Sapienza University of Rome); M. L. Mancusi (Catholic University (Milan) and CRIOS, Bocconi University); F. Sanna-Randaccio (Sapienza University of Rome); R. Sestini (Sapienza University of Rome); E. Verdolini (Fondazione CMCC and Fondazione Eni Enrico Mattei) |
| Abstract: | A major concern regarding innovation in clean technologies in the EU is that the fragmentation of its innovation system may hinder knowledge flows and, consequently, spillovers across member countries. A low intensity of knowledge flows across EU states can negatively impact their technological base, suppressing opportunities for further innovations and hindering the movement towards the technological frontier. This paper evaluates the fragmentation of the EU innovation system in the field of renewable energy sources (RES) by examining the intensity and direction of knowledge spillovers over the years 1985-2010. We modify the original double exponential knowledge diffusion model to provide information on the degree of integration of EU countries’ innovation efforts and to assess how citation patterns changed over time. We show that EU RES inventors have increasingly built “on the shoulders of the other EU giants”, intensifying their citations to other member countries and decreasing those to domestic inventors. Furthermore, the EU strengthened its position as source of RES knowledge for the US. Finally, we show that this pattern is peculiar to RES, with other traditional (i.e. fossil-based) energy technologies behaving in a completely different way. |
| Keywords: | Knowledge Spillovers, Renewable Energy Technologies, Fossil Energy Technologies, EU Innovation |
| JEL: | Q55 Q58 Q42 O31 O33 |
| Date: | 2016–12 |
| URL: | http://d.repec.org/n?u=RePEc:fem:femwpa:2016.71&r=knm |
| By: | Wanzenböck, Iris; Piribauer, Philipp |
| Abstract: | In this paper we estimate space-time impacts of the embeddedness in R&D networks on regional knowledge production by means of a dynamic spatial panel data model with non-linear effects for a set of 229 European NUTS-2 regions in the period 1999-2009. Embeddedness refers to the positioning in networks where nodes represent regions that are linked by joint R&D endeavours in European Framework Programmes. We observe positive immediate impacts on regional knowledge production arising from increased embeddedness in EU funded R&D networks, in particular for regions with lower own knowledge endowments. However, long-term impacts of R&D network embeddedness are comparatively small.(authors' abstract) |
| Keywords: | R&D networks; European Framework Programme; regional knowledge production; dynamic spatial panel data model; space-time impacts |
| Date: | 2015–09 |
| URL: | http://d.repec.org/n?u=RePEc:wiw:wus005:4652&r=knm |
| By: | Binsfeld, Nico; Whalley, Jason; Pugalis, Lee |
| Abstract: | There is growing awareness amongst policy makers, scholars and practitioners that the Information and Communication Technology (ICT) sector plays an important role in a country's economy and welfare. The ICT sector relies on highly performing technical infrastructures but also needs skilled people who are able to understand its complexities and are fully capable of making the best use of its potential. In this article we present and discuss this tension for the case of Luxembourg, one of the smallest countries in the world whose economy is open and largely service driven. Although a lot of improvements have been made in recent years regarding its ICT infrastructure, Luxembourg performs poorly in international league tables with regards to e-skills or digital competences showing a tendency to a “second level digital divide” in terms of its ICT professionals. Drawing on a prior study which mapped Luxembourg's ICT ecosystem, we conducted qualitative interviews with human resources managers that allowed us to identify the need for relevant ICT professional skills. By applying an e-competences framework, we have identified six different families of ICT jobs that are most demanded in Luxembourg as well as their underlying competences. We then present several policy initiatives that could address the challenges faced by Luxembourg. By doing so we provide a contribution in order to better understand the issues related to e-skills and digital competences in a small country. To the best of our knowledge this is the first study of this kind looking specifically into the e-skills situation in Luxembourg |
| Keywords: | e-skills,digital divide,competences frameworks,Luxembourg,ICT |
| Date: | 2016 |
| URL: | http://d.repec.org/n?u=RePEc:zbw:itse16:148660&r=knm |
| By: | Sadowski, Bert; Nomaler, Onder; Whalley, Jason |
| Abstract: | The Internet-of-things (IoT) has been heralded as the third industrial revolution combining disruptive technological change and a radical restructuring of the traditional ICT ecosystem. Technological diversification allows companies in the information and communication technology (ICT) industries to participate in the IoT by transplanting their existing know-how to new application domains. In using the ICT ecosystem perspective, this paper examines the diversification of 1323 ICT companies into IoT by investigating 86,159 main patents in the IoT area using the USPTO database. The paper examines the extent to which the existing knowledge base allows ICT firms to diversify into the new technological area, that is, IOT. It utilizes an entropy measure to characterize the extent to which ICT firms diversify into IoT. We propose that a firm's knowledge position in a new emerging technological has an important strategic value in terms of competitiveness. It characterizes a few new application domains in neighboring industries like health or transport. The paper concludes that due to technological pervasiveness Iot provides for new innovative activities and technological opportunities for ICT companies to grow in emerging sectors like wearables, industrial automation, smart energy and smart mobility. |
| Date: | 2016 |
| URL: | http://d.repec.org/n?u=RePEc:zbw:itse16:148701&r=knm |