Publications
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PDF Diversity in one dimension alongside greater similarity in others: Evidence from FP7 cooperative research teams
Although diversity between team members may bring benefits of new perspectives, nevertheless, what holds a team together is similarity. We… Show more theorise that diversity in one dimension is traded off against diversity in another. Our analysis of collaborative research teams that received FP7 funding presents robust results that indicators of diversity in several dimensions (diversity of organizational form (universities, firms, etc.), diversity in nationality and inequality in project funding share) are negatively correlated with each other. Show less
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PDF The 2016 Survey on R&D Investment Business Trends
The EU R&D Survey is a yearly survey amongst the top 1000 EU-based R&D investing companies from the R&D Scoreboard.… Show more The 157 participating companies in this report declared a total R&D investment from their own resources of €59.3 billion in 2015, or one third of the total R&D investment by the 1000 companies of the 2015 EU Scoreboard. The main findings are as follows: The R&D investments expectation for the years 2016 & 17 is characterised by a decrease for big companies from the automobiles & parts sector (-0.8%). This is in stark contrast with the last two R&D Surveys where companies from this sector foresaw a healthy growth figure (around 4%) for the years 2014-15 and 2015-16. Positive expectations of R&D investments growth are the strongest in the high-tech sectors, specifically in Healthcare, Pharmaceuticals and Technology Hardware, with foreseen growth of around 7-8%. Overall the companies in the Survey expect R&D investments to grow by 1.4% p.a. as compared to 3.0% in last year's Survey. The decrease in growth expectations is mainly due to the above negative expectations in the automobiles sector, which weigh heavily on the overall sample. Without this effect, growth expectations would have been 3.8%. Growth expectations also vary by world region. The EU is the region where the lowest growth is to be expected (0.5%). India (10%), the rest of the world (4.6%) and non-EU European countries (4.5%) expect the highest growth. China shows a striking difference with previous years having passed from double digit expectations to a mere 3.1% due to shrinkage in the automobiles & parts sector. Without the companies from the automobiles & parts sector, the expectations for China would be 8 percentage points higher (11.5%) as well as 2 percentage points higher for all the other world regions. Companies tend to concentrate R&D activities in fewer locations than production activities: 34% of the companies perform R&D in 1 or 2 locations, while for production this is only 17%. The automobiles & parts sector remains the largest employer for highly-skilled workers in the EU. The sectors aerospace & defence, chemicals, oil & gas producers are characterised by a high share of R&D employees as of total employees. Labour costs are rather unimportant for deciding the location of R&D or production activities. Companies attach much more value to high availability of personnel and knowledge, access to (economically and politically stable) markets and proximity to other activities within the company. Regarding the Commission's structural reforms being pursued, the respondents see a higher potential of product market reforms and market regulation for increasing their R&D and innovation than labour market reforms. Show less
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PDF Sector dynamics and demographics of top R&D firms in the global economy
This paper investigates the sectoral dynamics of the major economies during the last decade through the lens of the top… Show more 1000 R&D investors worldwide and looks at how firms' demographics are related to sector distribution. In doing so, it contributes to the literature on the EU corporate R&D intensity gap as well as on that on industrial dynamics. Contrary to the common understanding, the results show that in the EU the distribution of R&D among sectors has changed more than in the USA, which has experienced a shift mainly towards ICT-related sectors. In both the EU and the USA the pace of R&D change is slower than in the emerging economies. Furthermore, the EU has been better able than the USA and Japan to maintain its world share of R&D investment. Even more interestingly, the results show that age is strongly related to the sector (and dominant technology) in which firms operate. This suggests that focusing on sector (technological) dynamics could be even more relevant from a policy perspective than focusing only on young leading innovators. In fact, EU firms are less able to create or enter new high-tech sectors in a timely way and fully exploit the growth opportunities offered by first mover advantages. Show less
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PDF Technological diffusion as a recombinant process
In this work we analyse patterns of technological development using patent applications at the United States Patent and Trademark Office… Show more (USPTO) over the 1973-2012 period. Our study focuses on the combinations of technological fields within patent documents and their evolution in time, which can be modelled as a diffusion process. By focusing on the combinatorial dimension of the process we obtain insights that complement those from counting patents. Our results show that the density of the technological knowledge network increased and that the majority of technological fields became more interconnected over time. We find that most technologies follow a similar diffusion path that can be modelled as a Logistic or Gompertz function, which can then be used to estimate the time to maturity defined as the year at which the diffusion process for a specific technology slows down. This allows us to identify a set of promising technologies which are expected to reach maturity in the next decade. Our contribution represents a first step in assessing the importance of diffusion and cross-fertilization in the development of new technologies, which could support the design of targeted and effective Research and Innovation and Industrial policies. Show less
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PDF The 2016 EU Industrial R&D Investment Scoreboard
The 2016 edition of the EU Industrial R&D Investment Scoreboard (the Scoreboard) analyses the 2500 companies investing the largest sums… Show more in R&D in the world in the fiscal year 2015/16. It comprises companies based in the EU (590), the US (837), Japan (356), China (327), Taiwan (111), South Korea (75), Switzerland (58) and further 20 countries. Show less
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PDF The Specialisation of EU Regions in Fast Growing and Key Enabling Technologies
In the context of the Europe 2020 objective of establishing in the EU a smart, sustainable and inclusive economy, European… Show more regions have been called to design and implement national and regional 'Research and Innovation Strategies for Smart Specialisation' (RIS3). The rationale behind the concept of smart specialisation is that, in a context of global competition for talent and resources, most regions can only acquire a real competitive edge by finding niches or by mainstreaming new technologies into traditional industries and exploiting their ‘smart' regional potential. Although the most promising way for a region to promote its knowledge-based growth is to diversify into technologies, products and services that are closely related to existing dominant technologies and the regional skills base, the European Commission puts special emphasis on a set of technologies labelled as 'Key Enabling Technologies' (KETs). Despite the great emphasis on KETs, there is only very limited evidence on the capability of EU regions to specialise in these fields and there are no studies directly investigating the actual impact of these technologies on regional innovation and economic growth. This report aims at filling these gaps by: i) looking at the relationship between KETs and 'Fast Growing Technologies' (FGTs); ii) providing empirical evidence on the EU regional specialisation in KETs and FGTs; iii) relating technological specialisation to regional innovation and economic growth. In particular, the report aims at answering these questions: 1) Which technologies have emerged as the fastest growing ones in the recent decades? 2) Is there a relationship between fast growing technologies and KETs? 3) Which regions are specialised in FGTs and KETs? 4) Are there convergence and polarization phenomena observable in the evolution of EU regions' innovative activities in fast growing technologies and KETs? 5) Do EU regions specialized in fastest growing technological fields and key enabling technologies exhibit higher innovation and economic performances? The main results of the report can be summarised as follows. First, only a small share of KETs are also fast growing technologies, although the degree of overlapping between KETs and FGTs varies substantially across different KETs fields. Second, while KETs are concentrated in Central Europe, FGTs prevail in Scandinavian countries and the UK. Third, while there is evidence of some regional convergence in KETs and, to a less extent, in FGTs, spatial correlation increases over time, showing that diffusion often occurs across contiguous regions. Finally, the results of the estimations of the effects of FGTs and KETs on innovation (patents) and economic (GDP per capita) growth show that only specialisation in KETs directly affects economic growth, while specialisation in FGTs has an impact on growth only indirectly, that is through its impact on regions' innovation performances. Overall, these results confirm the pervasive and enabling role of KETs pointing to the importance for European regions to target these technologies as part of their RIS3 strategies. Show less
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PDF Industrial Research and Innovation: Evidence for Policy
This policy brief addresses the results of the fifth European Conference on Corporate R&D and Innovation CONCORDi 2015, on 'Industrial… Show more Research and Innovation: evidence for policy'. Taking stock from the underlined background issues, the document presents the main evidence-based insights for policy drawing upon the contributions and debates. It also highlights the main implications for industrial and innovation policies making and for the science-policy interface. A series of open questions for policy and evidence makers conclude the brief. Show less
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Quantitative Analysis of Technology Futures: A Review of Techniques, Uses and Characteristics. Science and Public Policy, forthcoming. DOI:10.1093/scipol/scv059
A variety of quantitative techniques have been used in the past in future-oriented technology analysis (FTA). In recent years, increased… Show more computational power and data availability have led to the emergence of new techniques that are potentially useful for foresight and forecasting. As a result, there are now many techniques that might be used in FTA exercises. This paper reviews and qualifies quantitative methods for FTA in order to help users to make choices among alternative techniques, including new techniques that have not yet been integrated into the FTA literature and practice. We first provide a working definition of FTA and discuss its role, uses and popularity over recent decades. Second, we select the most important quantitative FTA techniques, discuss their main contexts and uses, and classify them into groups with common characteristics, positioning them along key dimensions: descriptive/prescriptive, extrapolative/normative, data gathering/inference, and forecasting/foresight. Show less
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Barriers to innovation and firm productivity. Economics of Innovation and New Technology, Vol. 25, Issue 3, pp. 321-334. DOI:10.1080/10438599.2015.1076193
The paper analyzes the effect of financial, knowledge, demand, market structure and regulation barriers to innovation on firms' economic performance.… Show more It contributes to the literature on barriers to innovation by accounting for the heterogeneous effects that each barrier has on firms across the productivity distribution. We do so by employing both quantile regression techniques and matching estimators on this UK CIS panel 2002–2010 merged with the Business Structure Database. While we find evidence that both the cost and also the availability of finance negatively affect productivity across the whole distribution, the lack of qualified personnel mostly hinders high productivity firms. Moreover, quantile regression reveals some interesting variation in effect sizes across the (conditional) productivity distribution. Show less