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on Innovation |
| By: | Filippo Mezzanotti; Timothy Simcoe |
| Abstract: | It is more than 25 years since the authors of the Yale and Carnegie surveys studied how firms seek to protect the rents from innovation. In this paper, we revisit that question using a nationally representative sample of firms over the period 2008-2015, with the goal of updating and extending a set of stylized facts that has been influential for our understanding of the economics of innovation. There are five main findings. First, while patenting firms are relatively uncommon in the economy, they account for an overwhelming share of R&D spending. Second, utility patents are considered less important than other forms of IP protection, like trade secrets, trademarks, and copyrights. Third, industry differences explain a great deal of the level of firms’ engagement with IP, with high-tech firms on average being more active on all forms of IP. Fourth, we do not find any significant difference in the use of IP strategies across firms at different points of their life cycle. Lastly, unlike age, firms of different size appear to manage IP significantly differently. On average, larger firms tend to engage much more extensively in the protection of IP, and this pattern cannot be easily explained by differences in the type of R&D or innovation produced by a firm. We also discuss the implications of these findings for innovation research and policy. |
| Date: | 2022–03 |
| URL: | http://d.repec.org/n?u=RePEc:cen:wpaper:22-09&r= |
| By: | Stern, Nicholas; Sivropoulos-Valero, Anna Valero |
| Abstract: | The climate crisis and the global economic impact of the Covid-19 crisis occur against a background of slowing growth and widening inequalities, which together imply an urgent need for a new environmentally sustainable and inclusive approach to growth. Investments in "clean" innovation and its diffusion are key to shaping this, accompanied by investments in complementary assets including sustainable infrastructure, and human, natural and social capital which will not only help achieve net-zero greenhouse gas emissions, but will also improve productivity, living standards and the prospects of individuals. In this article, we draw on the theoretical and empirical evidence on the opportunities, drivers and policies for innovation-led sustainable growth. We highlight the importance of a coordinated set of long-term policies and institutions that can enable and foster private sector investments in clean innovation and assets quickly and at scale. In doing so, we draw inspiration from Chris Freeman's work on the system-wide drivers of innovation, and his early vision of achieving environmental sustainability by reorienting growth. |
| Keywords: | innovation; sustainable growth; net-zero transition; clean technology; ES/S001735/1 |
| JEL: | O31 O33 O38 O55 |
| Date: | 2021–06–01 |
| URL: | http://d.repec.org/n?u=RePEc:ehl:lserod:114385&r= |
| By: | Kroll, Henning; Frietsch, Rainer |
| Keywords: | China,Global Science,Innovation |
| Date: | 2022 |
| URL: | http://d.repec.org/n?u=RePEc:zbw:fisidp:73&r= |
| By: | LEOGRANDE, ANGELO |
| Abstract: | The European Innovation Scoreboard-EIS calculates the value of employees in knowledge-intensive activities in Europe. |
| Keywords: | Innovation, and Invention: Processes and Incentives; Management of Technological Innovation and R&D; Diffusion Processes; Open Innovation. |
| JEL: | O30 O31 O32 O33 O34 |
| Date: | 2022–03–24 |
| URL: | http://d.repec.org/n?u=RePEc:pra:mprapa:112538&r= |
| By: | LEOGRANDE, ANGELO |
| Abstract: | The European Innovation Scoreboard calculates the value of the impact of innovation on employment through the sum of two sub-indicators, i.e. employment in knowledge-intensive activities and employment in innovative companies. |
| Keywords: | Innovation, and Invention: Processes and Incentives; Management of Technological Innovation and R&D; Diffusion Processes; Open Innovation. |
| JEL: | O30 O31 O32 O33 O34 |
| Date: | 2022–03–23 |
| URL: | http://d.repec.org/n?u=RePEc:pra:mprapa:112517&r= |
| By: | Neuhäusler, Peter; Rothengatter, Oliver |
| Abstract: | In this study, we contribute to the evaluation of the performance of the German science and research system by analyzing the dynamics of transnational patent filings of German inventors in an international comparison over the past 20 years. Besides country-specific analyses, we further differentiate our findings by 38 high-technology fields including aggregate categories (high-level, leading-edge and less R&D intensive technologies). In addition to country comparisons, which are analyzed in each years' report of this series, we also provide international co-patenting trends, dig deeper into regionalized patent statistics by analyzing patent activities of the German federal states. In a final step, we take a closer look at patent dynamics in the public research sector. |
| Date: | 2022 |
| URL: | http://d.repec.org/n?u=RePEc:zbw:efisdi:42022&r= |
| By: | Luca Verginer; Federica Parisi; Jeroen van Lidth de Jeude; Massimo Riccaboni |
| Abstract: | In high-tech industries, where intellectual property plays a crucial role, the acquisition of intangible assets and employees' tacit knowledge is an integral part of the motivation for Mergers and Acquisitions (M&As). Following the molecular biology revolution, the wave of takeovers in the biotechnology industry in the Nineties is a well-known example of M&As to absorb new knowledge. The retention of critical R&D employees embodying valuable knowledge and potential future innovation is uncertain after an acquisition. While not all employees might be relevant for the success of the takeover, inventors are among the most valuable. This is especially true for the acquisition of an innovative start-up. This paper estimates how likely an inventor working for an acquired biotechnology company will leave. We find that inventors affected by acquisitions are 20\% more likely to leave the company by a difference-in-differences approach matching both firms and inventors. |
| Date: | 2022–03 |
| URL: | http://d.repec.org/n?u=RePEc:arx:papers:2203.12968&r= |
| By: | Gergõ Tóth (Agglomeration and Social Networks Lendület Research Group, Centre for Economic and Regional Studies, Tóth Kálmán u. 4, 1097 Budapest, Hungary and Spatial Dynamics Lab, University College Dublin, D04 V1W8, Dublin, Ireland); Zoltán Elekes (Agglomeration and Social Networks Lendület Research Group, Centre for Economic and Regional Studies, Tóth Kálmán u. 4, 1097 Budapest, Hungary and Centre for Regional Science at Umea University, Umea University, 901 87 Umea, Sweden); Adam Whittle (Spatial Dynamics Lab, University College Dublin, D04 V1W8, Dublin, Ireland); Changjun Lee (Spatial Dynamics Lab, University College Dublin, D04 V1W8, Dublin, Ireland andDepartment of Media and Social Informatics, Hanyang University, Ansan-si, South Korea); Dieter F. Kogler (Spatial Dynamics Lab, University College Dublin, D04 V1W8, Dublin, Ireland Insight Centre for Data Analytics, University College Dublin, Belfield, Dublin 4, Ireland) |
| Abstract: | This paper assesses the network robustness of the technological capability base of 269 European metropolitan areas against the potential elimination of some of their capabilities. By doing so it provides systematic evidence on how network robustness conditioned the economic resilience of these regions in the context of the 2008 economic crisis. The analysis concerns calls in the relevant literature for more in-depth analysis on the link between regional economic network structures and the resilience of regions to economic shocks. By adopting a network science approach that is novel to economic geographic inquiry, the objective is to stress-test the technological resilience of regions by utilizing information on the co-classification of CPC classes listed on European Patent Office patent documents. We find that European metropolitan areas show heterogeneous levels of technology network robustness. Further findings from regression analysis indicate that metropolitan regions with a more robust technological knowledge network structure exhibit higher levels of resilience with respect to changes in employment rates. This finding is robust to various random and targeted elimination strategies concerning the most frequently combined technological capabilities. Regions with high levels of employment in industry but with vulnerable technological capability base are particularly challenged by this aspect of regional economic resilience. |
| Keywords: | regional economic resilience, network robustness, metropolitan regions, technology space |
| JEL: | C53 O30 R11 |
| Date: | 2022–01 |
| URL: | http://d.repec.org/n?u=RePEc:has:discpr:2202&r= |
| By: | Leogrande, Angelo; Magaletti, Nicola; Cosoli, Gabriele; Giardinelli, Vito; Massaro, Alessandro |
| Abstract: | The following article estimates the value of ICT Specialists in Europe between 2016 and 2021 for 28 European countries. The data were analyzed using the following econometric techniques, namely: Panel Data with Fixed Effects, Panel Data with Random Effects, WLS and Pooled OLS. The results show that the value of ICT Specialists in Europe is positively associated with the following variables: "Desi Index", "SMEs with at least a basic level of digital intensity", "At least 100 Mbps fixed BB take-up" and negatively associated with the following variables: "4G Coverage","5G Coverage", "5G Readiness", "Fixed broadband coverage", "e-Government", "At least Basic Digital Skills", "Fixed broadband take-up", "Broadband price index", "Integration of Digital Technology". Subsequently, two European clusters were found by value of "ICTG Specialists" using the k-Means clustering algorithm optimized by using the Silhouette coefficient. Finally, eight different machine learning algorithms were compared to predict the value of "ICT Specialists" in Europe. The results show that the best prediction algorithm is ANNArtificial Neural Network with an estimated growth value of 12.53%. Finally, "augmented data" were obtained through the use of the ANN-Artificial Neural Network, through which a new prediction was made which estimated a growing value of the estimated variable equal to 3.18%. |
| Keywords: | Innovation, and Invention: Processes and Incentives; Management of Technological Innovation and R&D; Diffusion Processes; Open Innovation. |
| JEL: | O30 O31 O32 O33 O34 |
| Date: | 2022–03–05 |
| URL: | http://d.repec.org/n?u=RePEc:pra:mprapa:112241&r= |
| By: | Leogrande, Angelo; Magaletti, Nicola; Cosoli, Gabriele; Massaro, Alessandro |
| Abstract: | In this article the value of “Fixed Broadband Take Up” in Europe is investigated. Data are collected from the DESI-Digital Economy and Society Index for 28 countries in the period 2016-2021. Data are analyzed with Panel Data with Fixed Effects and Random Effects. The Fixed Broadband Take-Up value is positively associated with the value of "Connectivity", "Human Capital", "Desi Index", "Fast BB NGA Coverage", "Fixed Very High-Capacity Network VHCN coverage". Fixed Broadband Take-Up value is negatively associated with "Digital Public Services for Businesses", "e-Government", "At least Basic Digital Skills", "At Least Basic Software Skills", "Above Basic Digital Skills", "Advanced Skills and Development", "Integration of Digital Technology", "Broadband Price Index", "Mobile Broadband", "Fixed Broadband Coverage". Subsequently the k-Means algorithm optimized by the Silhouette coefficient was used to identify the number of clusters. The analysis shows the presence of the two clusters. Eight different machine learning algorithms were then used to predict the future value of the "Fixed Broadband Take-Up in Europe". The analysis shows that the most efficient algorithm for the prediction is "ANN-Artificial Neural Network" with an estimated value of the prediction equal to 26.39%. |
| Keywords: | nnovation, and Invention: Processes and Incentives; Management of Technological Innovation and R&D; Diffusion Processes; Open Innovation. |
| JEL: | O3 O30 O31 O32 O33 O34 |
| Date: | 2022–03–05 |
| URL: | http://d.repec.org/n?u=RePEc:pra:mprapa:112246&r= |
| By: | Hirvonen, Johannes; Stenhammar, Aapo; Tuhkuri, Joonas |
| Abstract: | Abstract We present novel evidence on the effects of advanced technologies on employment, skill demand, and firm performance. The main finding is that advanced technologies led to increases in employment and no change in skill composition. Our main research design focuses on a technology subsidy program in Finland that induced sharp increases in technology investment in manufacturing firms. Our data directly measure multiple technologies and skills and track firms and workers over time. We demonstrate novel text analysis and machine learning methods to perform matching and to measure specific technological changes. To explain our findings, we outline a theoretical framework that contrasts two types of technological change: process versus product. We document that firms used new technologies to produce new types of output rather than replace workers with technologies within the same type of production. The results contrast with the ideas that technologies necessarily replace workers or are skill biased. |
| Keywords: | Technology, Labor, Skills, Industrial policy |
| JEL: | J23 J24 O33 |
| Date: | 2022–04–11 |
| URL: | http://d.repec.org/n?u=RePEc:rif:wpaper:93&r= |
| By: | Leogrande, Angelo; Magaletti, Nicola; Cosoli, Gabriele; Massaro, Alessandro |
| Abstract: | The following article analyzes the determinants of e-government in 28 European countries between 2016 and 2021. The DESI-Digital Economy and Society Index database was used. The econometric analysis involved the use of the Panel Data with Fixed Effects and Panel Data with Variable Effects methods. The results show that the value of “e-Government” is negatively associated with “Fast BB (NGA) coverage”, “Female ICT specialists”, “e-Invoices”, “Big data” and positively associated with “Open Data”, “e-Government Users”, “ICT for environmental sustainability”, “Artificial intelligence”, “Cloud”, “SMEs with at least a basic level of digital intensity”, “ICT Specialists”, “At least 1 Gbps take-up”, “At least 100 Mbps fixed BB take-up”, “Fixed Very High Capacity Network (VHCN) coverage”. A cluster analysis was carried out below using the unsupervised k-Means algorithm optimized with the Silhouette coefficient with the identification of 4 clusters. Finally, a comparison was made between eight different machine learning algorithms using "augmented data". The most efficient algorithm in predicting the value of e-government both in the historical series and with augmented data is the ANN-Artificial Neural Network. |
| Keywords: | Innovation, and Invention: Processes and Incentives; Management of Technological Innovation and R&D; Diffusion Processes; Open Innovation. |
| JEL: | O30 O31 O32 O33 O34 |
| Date: | 2022–03–05 |
| URL: | http://d.repec.org/n?u=RePEc:pra:mprapa:112242&r= |
| By: | Carlos G\'oes; Eddy Bekkers |
| Abstract: | Geopolitical conflicts have increasingly been a driver of trade policy. We study the potential effects of global and persistent geopolitical conflicts on trade, technological innovation, and economic growth. In conventional trade models the welfare costs of such conflicts are modest. We build a multi-sector multi-region general equilibrium model with dynamic sector-specific knowledge diffusion, which magnifies welfare losses of trade conflicts. Idea diffusion is mediated by the input-output structure of production, such that both sector cost shares and import trade shares characterize the source distribution of ideas. Using this framework, we explore the potential impact of a "decoupling of the global economy," a hypothetical scenario under which technology systems would diverge in the global economy. We divide the global economy into two geopolitical blocs -- East and West -- based on foreign policy similarity and model decoupling through an increase in iceberg trade costs (full decoupling) or tariffs (tariff decoupling). Results yield three main insights. First, the projected welfare losses for the global economy of a decoupling scenario can be drastic, as large as 15% in some regions and are largest in the lower income regions as they would benefit less from technology spillovers from richer areas. Second, the described size and pattern of welfare effects are specific to the model with diffusion of ideas. Without diffusion of ideas the size and variation across regions of the welfare losses would be substantially smaller. Third, a multi-sector framework exacerbates diffusion inefficiencies induced by trade costs relative to a single-sector one. |
| Date: | 2022–03 |
| URL: | http://d.repec.org/n?u=RePEc:arx:papers:2203.12173&r= |