ICT innovation in Europe: Productivity gains, startup growth and retention A STUDY PREPARED BY IMPERIAL COLLEGE BUSINESS SCHOOL P. KOUTROUMPIS1, A. LEIPONEN2 AND L.D.W. THOMAS3 We acknowledge financial support from the EIT ICT Labs. We also wish to thank Achim Luhn for guidance and support and Kumush Abduraimova for research assistance. 1
Imperial College Business School Cornell University and Imperial College Business School 3
Imperial College Business School 2
1 EXECUTIVE SUMMARY Information and communication technologies (ICTs) are a core driver of the economy. The accelerating pace of technological progress continues to challenge our individual, societal and institutional responses and this adaptation process – or lack thereof – is responsible for the wide variation of ICT impact across countries. In this report we assess the relative impact of ICT innovations within Europe, identify regional champions, and highlight the path to grow and nurture innovative ICT businesses in Europe. The economic importance of ICT as a general-­‐purpose technology is well recognized. ICT innovation requires two types of inputs: resources (equipment, applications, talent, skills) and governance (organizational arrangements, management skills, and economic institutions, including regulation). ICT innovation continues to be relevant considering that the EU-­‐US productivity gap persists: comparable ICT investments combined with more intense competition, as well as flexible management practices and labor market institutions, have allowed US industries to more significantly increase their output than their EU peers. Nonetheless, one fifth of all economic growth in the EU during the period of 1995 to 2010 can be attributed to ICT investments. More recently (2005-­‐2010) this effect reached one third of all EU growth. In other words, ICT investments continue to drive overall economic development in Europe, and it is essential for European economies to recognize this and realize the full potential of the continuing dynamism of the ICT sector by encouraging innovation and enhancing entry and competition across the Euro-­‐zone. In both Europe and the United States, ICT firms themselves are the first to realize the gains from new ICT applications and investments. However, the gains from these ICT innovations spill over to a variety of adjacent sectors that differ vastly across the EU countries. For example, financial services in the UK and Netherlands, manufacturing in Germany, and electronics in Finland, have substantially benefited from ICT innovations both through increased investments and organizational restructuring. A possible reason for the apparent success of these sectors is that they are intensively engaged in global competition. In contrast, domestic and protected sectors that are little affected by foreign competition are much less likely to invest and benefit from state-­‐of-­‐the-­‐art ICT applications. ICT innovations are created in firms, universities, and research centers. The common factor in all these cases is intellectual capital, i.e. people. Due to their flexible structures and risk-­‐taking attitudes, small and young ICT firms in the EU spend orders of magnitude more funds relative to their size than large firms to conduct research and development for new products and services. Much of R&D investment is investment in knowhow and high-­‐level skills. Thus, European policies should continue to encourage the R&D flowing from small and young firms. In particular, it is important to consider whether R&D policies crowd out private investment by large firms or whether they truly encourage innovation by financially constrained firms – typically small and young firms – that otherwise would not have been able to invest. ICT innovations can to a degree be protected and capitalized upon through intellectual property (IP) rights. Patents are legal exclusion rights that represent one of the common ways to protect IP, and can be used to measure ICT hardware invention activity across nations. While patent data reveal that there is wide variation of inventive specialization among EU countries, Germany is the region’s invention powerhouse across most ICT patent classes. Beyond Germany’s dominance, the breadth of ICT specialization in Europe is remarkable. The exploitation of these specializations seems to diverge from the substantial innovative efforts within Europe. While there are consistently more innovation spillovers from ICT patents than other patent classes, EU countries have failed to capitalize on this technological advantage. 2 In line with these findings, innovation policies have shifted from more generic new firm creation (through R&D or startup subsidies) into creating high-­‐impact startups. The realization that a handful of new firms are responsible for the bulk of economic growth has led to the attempts to create “entrepreneurship ecosystems” focusing on business acceleration via incubation, advisory, and venture capital (VC) support. While one quarter of all accelerators in the world are located in Europe, the majority of such schemes lack intra-­‐sector coordination and a clear focus on systemic constraints (tax rates, financing, ease of doing business, etc.). VC has gradually started to flow in the UK -­‐ making London the sixth largest global tech hub – and to a lesser extent to other technology hubs in Europe. However the current rise of accelerators seems to overlook that 47%4 of successful EU startups end up being acquired by US companies. Thus, Europe to a striking extent misses out on the benefits from the growth and maturation of these high-­‐impact companies. A deeper analysis of all the reasons for such high-­‐growth venture flight, and urgent action to address them, should be policy priorities for countries associated with ICT Labs. Europe therefore is catching up to the US in idea creation and risk capital but is lacking the means to retain its talent at home. There are two main reasons for this, which also influence the relative scarcity of VC in Europe compared to the US: First, the fragmented European digital market poses substantial legal, regulatory, linguistic and cultural barriers for promising startups to scale. Second, the scarcity of skills and in some cases VC create real growth constraints for smaller firms residing in the region. If this trend is not tackled and reversed, the region will continue to supply the US with an extremely scarce resource – individuals capable of creating high-­‐growth firms. The process of growth through internationalization of innovative young ICT firms is another area where further analysis of the European market would be valuable. European tech startups have attracted more than USD$28 billion by US investors in the first 8 months of 2014. The economic value created by these firms is appropriated outside Europe given the difficulties to scale at home. Moreover, engineers and programmers are often better off joining an established ICT firm instead of proceeding with a new venture. This further reinforces the misallocation of talent to less high-­‐impact activities. Therefore, ensuring sufficient VC and IPO markets in European countries is a high-­‐priority policy initiative. To end Europe’s prolonged recession, an accelerated return to growth is deemed to be the cure. However, as long as European decision makers fail to understand the dynamics of successful startups, they can do little to induce growth and then reap the benefits. Furthermore, long-­‐term economic development depends on technological innovation and new ICTs continue to revolutionize industries and societies. It is thus critical for the future of Europe to address the shortcomings of the ICT innovation system in terms of commercializing and appropriating the returns on R&D investments. The EIT ICT Labs countries are in many ways ahead of the rest of Europe, but much remains to be done to enhance the governance of innovation. Our key takeaway is that EU countries – even the leading ones – need to further their efforts to fund and nurture innovative startups and individuals in Europe. To retain successful startups and individuals in Europe we recommend that policy makers mobilize and maintain a sustainable entrepreneurship ecosystem in Europe. Specific policy actions include: • Maintain and strengthen the commercialization of ideas by expanding and coordinating incubator and accelerator programs in the region. The current focus overlooks the potential for ideas that take longer to mature and materialize. 4
For the entire 2013 and 49% in terms of total USD value; for January to August 2014 this dropped to 43% of startups and 44% in terms of USD values. 3 •
•
•
Address systemic constraints across countries. These range from corporate and income taxation, access and conditions to financing (including VC), bankruptcy law and other sector-­‐specific bureaucratic processes within and across countries. Remove regulatory and entry barriers to support and enable firms to scale within Europe in one digital market of 0.5 billion customers instead of 28 separate ones. Two thirds of the European population resides in the five largest countries and this could be the first step in this direction. Connect and train innovators in Europe – there is much more to gain from joint efforts based on the remarkable research outputs of EU countries. 4 TABLE OF CONTENTS EXECUTIVE SUMMARY ............................................................................................................... 2 TABLE OF CONTENTS .................................................................................................................. 5 1.0 INTRODUCTION ............................................................................................................. 6 2.0 ICT PRODUCTIVITY ACROSS COUNTRIES ......................................................................... 8 2.1 Country Analysis .................................................................................................................. 8 2.1.1 Background on the productivity metrics .................................................................................. 10 2.1.2 Results ...................................................................................................................................... 11 2.2 Industry Analysis ................................................................................................................ 13 3.0 INNOVATION IMPACT OF ICT ....................................................................................... 16 3.1 ICT Innovation in firms ....................................................................................................... 16 3.1.1 ICT-­‐using firms .......................................................................................................................... 16 3.1.2 Research leading to innovation in firms ................................................................................... 17 3.1.3 Firm level analysis .................................................................................................................... 18 3.1.4 R&D Intensity ........................................................................................................................... 20 3.2 Patents ............................................................................................................................... 21 3.2.2 EU research specialization and leadership ............................................................................... 22 3.2.2 ICT innovation spillovers .......................................................................................................... 23 3.3 Venture Capital .................................................................................................................. 25 3.3.1 Background .............................................................................................................................. 26 3.3.2 Current trends for VC activity in the EU ................................................................................... 27 4.0 SUMMARY ................................................................................................................... 32 5.0 RECOMMENDATIONS ................................................................................................... 33 APPENDIX 1 – Methods ............................................................................................................ 36 APPENDIX 2 – ICT patents detail ............................................................................................... 37 APPENDIX 3 – VC by industry sector in Europe ......................................................................... 42 APPENDIX 4 – Databases used in this report ............................................................................. 43 5 1.0 INTRODUCTION The impact of information and communication technologies (ICTs) on business performance has shifted from invisibility (what was known as the “Solow Paradox”5) to the core economic driver of the Digitization age6 (or second machine age7). This change is attributed to the technological improvements that lead to paradigm shifts in the ways we communicate, work and entertain ourselves. The accelerating pace of technological progress continues to challenge our individual, societal and institutional responses and this adaptation process – or lack thereof – seems to be responsible for the wide variation of ICT impact across countries. In this report we look into the relative impact of ICT innovations within Europe, identify regional champions and highlight the path to retain innovative businesses in Europe. Building upon current understanding of the determinants of the ICT productivity divide between Europe and the US over the past decades, we argue that resources alone are not sufficient to fully capture the benefits from new technologies. By resources we refer to the prerequisite inputs necessary for ICT to be developed and adopted: for example, income and living standards allow individuals and businesses to buy new products and services; educational attainment of the local population lets people to make the most of new technologies; research centers, universities and technology hubs train people to produce new products and services. Governance Resources Value Although resources are essential for ICT value creation, governance is also necessary to capitalize the potential gains from these technologies. Our use of governance is broad and stems from national-­‐level policies spreading to firm strategies: the quality of institutions at the national and regional level; the openness of the economy and the free exchange of ideas; the adherence of management practices to facilitate change and adapt to new standards; the organizational flexibility that understands new capabilities and repositions labor capital in an optimal structure; the meritocracy at the private and public sectors. Governance has a multiplier effect on the added value of ICT. A corrupt state can realize some gains from the use of new technologies but will never allow 5
R Solow, "We'd Better Watch Out," New York Times Book Review, July 12 1987. R L Katz and P Koutroumpis, "Measuring Socio-­‐Economic Digitization: A Paradigm Shift," in Working Paper (2013). 7
E Brynjolfsson and A McAfee, The Second Machine Age: Work, Progress, and Prosperity in a Time of Brilliant Technologies (New York, NY: W W Norton & Company, Inc, 2014). 6
6 competition to freely work and new ideas to flourish. Similarly firms that resist change in light of technological improvements will be left behind their global competitors. While resources and governance are essential for the creation of value from ICTs, the distribution of this generated value requires investigation. Although the impact of innovative startups on the global economy is rarely challenged, there is an increasing concern that these benefits are not evenly – if at all – distributed to everyone. This new divide – through labor substitution and skill acquisition – that ICT innovations bring can be controlled and reduced by governance that facilitates further technological innovations. This report is structured as follows. In the second section we review ICT productivity across EU counties, investigating both at the country and industry levels of analysis. In the third section we consider the innovation impact of ICT, looking at the implications of ICT creation through firm R&D, patenting and commercialization of innovation through venture capital-­‐funded firms. We also investigate the rates of ICT innovation and consider firm-­‐level R&D, patents and VC investments. We conclude this section with an investigation of VC activity within the EU. The following section summarizes our results. We conclude with recommendations. 7 2.0
ICT PRODUCTIVITY ACROSS COUNTRIES In this section we review ICT productivity across EU counties, investigating both at the country and industry levels of analysis. 2.1 Country Analysis The link between ICTs and productivity at the national level has mainly focused on two areas: firstly, on the ways that ICT investments affect the performance of existing infrastructures; and secondly, on their impact on labor productivity. The earliest studies addressing the Solow Paradox have generally used growth accounting methods that decompose the different sources of productivity growth in an economy, such as labor and capital, so that the unexplained part of growth in GDP can then be taken to represent increases in productivity. Put differently, growth accounting techniques enable estimation of the contribution in percentage points of ICT investments to GDP growth. Some early growth accounting studies showed that the Solow paradox was more illusory than real as the level of ICT capital was simply low (2% of total capital circa 1993) and hence its impact could not be identified in the estimations.8 Later on, most OECD countries (Australia, Canada, Finland, France, Germany, Italy, Japan, UK, and the US) started to experience a marked increase in the rate of investment in ICT capital goods from 1980 to 2000.9 However, concurrent with the rise in demand for ICT investment, prices for ICT capital goods fell in relative and absolute terms, leading to substitution effects towards ICT capital goods and away from other factors of production. Software prices fell by less than ICT equipment prices, but this did not prevent rapid accumulation of software capital. In fact, the late 1990s was marked with a surge in ICT capital investment across G7 economies.10 In terms of the effect of ICT investment on productivity, studies have demonstrated a strong positive influence.11 For instance, ICT investment accounted for 1.1% of the 4.8% productivity growth rate during 1996-­‐1999, in contrast to an earlier ICT contribution of 0.5-­‐0.6% between 1974-­‐1995; the authors of this study argued that these results remain valid despite the dot-­‐com bubble. 12 Across OECD countries, ICT investments contributed between 0.2% to 0.5% to productivity growth, with the contribution rising to 0.3% to 0.9% per year in the second half of the 1990s.13 From a European perspective, and in particular for the UK, ICT contribution to GDP growth increased from 13.5% in 1979-­‐1989 to 20.7% in 1989-­‐1998, and ICT contribution of capital deepening rose from 55% 90%.14 In Finland, the contribution of ICTs to output growth increased from 0.3% in the early 1990s to 0.7% in the late 1990s, and the fast growth of total-­‐factor productivity in the ICT-­‐producing industries had 8
S D Oliner and D E Sichel, "Computers and Output Growth Revisited: How Big Is the Puzzle?," Brookings Papers on Economic Activity 2 (1994). 9
A Colecchia and P Schreyer, "ICT Investment and Economic Growth in the 1990s: Is the United States a Unique Case?," Review of Economic Dynamics 5, no. 2 (2002). 10
D W Jorgenson, "Information Technology and the G7 Economies," in Hard-­‐to-­‐Measure Goods and Services: Essays in Honor of Zvi Griliches, ed. E R Berndt and C R Hulten (Chicago, IL: University of Chicago Press, 2007). 11
More recent work has considered adjusting the ICT investment figures for quality so as to enable improved cross country harmonization; for an example see Corrado et al (2012). 12
S D Oliner and D E Sichel, "The Resurgence of Growth in the Late 1990s: Is Information Technology the Story?," Journal of Economic Perspectives 14, no. 1 (2000); "Information Technology and Productivity: Where Are We Now and Where Are We Going?," Federal Reserve Bank of Atlanta Review 87, no. 3 (2002). 13
Colecchia and Schreyer, "ICT Investment and Economic Growth in the 1990s: Is the United States a Unique Case?." 14
N Oulton, "ICT and Productivity Growth in the United Kingdom," Oxford Review of Economic Policy 18, no. 3 (2002). These percentages reflect the effect on growth not output hence the large differences compared to previously reported findings. 8 an even larger impact.15 More recently, in 2011 there has been further evidence of positive and significant productivity effects of ICT in Europe, mainly due to advances in total factor productivity, despite a negative macro-­‐economic shock not related to ICT.16 A major theme within this literature has been to document the difference between US and European productivity performance. The key observation is that the EU as a whole lagged behind the US throughout most of the 1990s, but then partially caught up in 1998-­‐2001. In 2001 about two thirds of the EU population was close to the US levels of ICT adoption, but there remained a group of “slow ICT adopters” (specifically Ireland, Italy, Spain, Portugal and Greece) whose lag in ICT investment has not decreased over time.17 Across OECD countries, the US, Australia, Finland and Canada experienced greater productivity growth than France, Italy, Germany and the UK during the 1990s. In a nutshell, the US-­‐EU productivity differential has evolved in three phases.18 In the first phase (1950-­‐1973), the EU GDP per capita grew more quickly than that of the US leading to a period of catch-­‐up; technology imitation and the influence of new post-­‐war institutions (such as those related to wage bargaining) were the key factors behind this phase. In the second phase of 1973-­‐1995, there was a slower rate of catch-­‐up, which is partly attributed to slower employment growth and a subsequent increase in capital intensity. The most recent phase, from 1995-­‐2006, was marked by a significant slowdown in EU productivity with average GDP growth per capita running at 1.5% for the EU and 2.3% for the US. While the US-­‐EU productivity differential is generally accepted, some scholars have claimed that it is simply a matter of time before Europe starts to catch up again,19 while others point to longer-­‐term structural issues in Europe such as over regulated labor and product markets.20 Moving from the national to industry level analyses one easily spots the difference between ICT-­‐producing and ICT-­‐
using sectors within an economy.21 There is a broad consensus that the earlier productivity benefits appear in the ICT-­‐producing industries and gradually spillover to ICT-­‐using sectors. In the late 1990s until the peak of the dot-­‐com crash most productivity growth came from ICT producing sectors and the massive investments in ICT using ones. However, from 2000 onwards, ICT production appears to be less important and this productivity growth is instead coming from intensive ICT-­‐users.22 Returning to the US-­‐EU differential, it has been shown that the productivity gap can be found in both ICT-­‐producing and ICT-­‐use sectors, for example, a difference of 1.3% between the EU (0.5%) and in the US (1.8%) for market services (an ICT-­‐using sector).23 15
J Jalava and M Pohjola, "Economic Growth in the New Economy: Evidence from Advanced Economies," Information Economics and Policy 14, no. 2 (2002). 16
C M Dahl, H C Kongsted, and A Sørensen, "ICT and Productivity Growth in the 1990s: Panel Data Evidence on Europe," Empirical Economics 40, no. 1 (2011). 17
F Daveri, "The New Economy in Europe, 1992-­‐2001," Oxford Review of Economic Policy 18, no. 3 (2002). 18
B van Ark, M O'Mahony, and M P Timmer, "The Productivity Gap between Europe and the United States: Trends and Causes," Journal of Economic Perspectives 22, no. 1 (2008)., 19
O Blanchard, "The Economic Future of Europe," ibid.18, no. 4 (2004). 20
C Gust and J Marquez, "International Comparisons of Productivity Growth: The Role of Information Technology and Regulatory Practices," Labour Economics 11, no. 1 (2004); J Van Reenen et al., "The Economic Impact of ICT," in Final Report (London, UK: Center for Economic Performance, London School of Economics, 2010). 21
R H McGuckin and K J Stiroh, "Do Computers Make Output Harder to Measure?," Journal of Technology Transfer 26, no. 4 (2001). 22
D W Jorgenson, M S Ho, and K J Stiroh, "A Retrospective Look at the US Productivity Resurgence," Journal of Economic Perspectives 22, no. 1 (2008)., D W Jorgenson et al., "Industry Origins of the US Productivity Resurgence," Economic Systems Research 19, no. 3 (2007). 23
van Ark, O'Mahony, and Timmer, "The Productivity Gap between Europe and the United States: Trends and Causes." 9 However, although there has been much research into the sources of the productivity differential between EU and the US, there is less research into intra-­‐EU variation. Earlier studies have shown that the larger European countries, namely Germany, France, the UK and Italy, and to a lesser extent Spain, account for the largest contributions to EU productivity growth.24 In terms of ICT-­‐producing sectors, these contributions have changed over time, with only the UK showing an increasing contribution to overall EU growth. In contrast, the contributions of France and Germany were initially declining in the 1980s and then increasing in the 1990s, while Italy showed the opposite pattern. Ireland, the Netherlands and Finland show large increases in their contributions in the late 1990s too. Considering the ICT-­‐using sectors, the UK again shows an increase in its contribution through time, while France and Germany show marked declines comparing the 1980s and late 1990s with Italy showing no change overall but a marked decline post 1995. The large increase in Spain’s contribution is the most notable with only small percentage point changes for the other member states. Beyond these findings, there is little that has considered these in the context of intra-­‐European variance. As such, we empirically investigate investment in ICT capital and productivity gains across EU countries. In doing so we highlight different approaches by sectoral composition, particularly looking to differences between ICT-­‐producing and ICT-­‐using sectors. 2.1.1 Background on the productivity metrics An abundance of methodological variations can be found in previous work. These include some standard growth accounting including a Cobb-­‐Douglas production function, total factor productivity and labor productivity equations, diffusion of technology models, structural models, simple correlations, meta-­‐analyses of models from previous studies, and others. Most of these methodological variations reflect the ongoing need for harmonization of the data published by various statistical agencies across Europe and the OECD. By and large researchers aim to ensure that some comparability of the findings is possible keeping in mind the bureaucratic inertia, the different reporting and accounting standards as well as the temporal effects (elections, crises, etc.) that may bias their results. Very few studies manage to adequately control for all these limitations and confounding effects as they are often restricted by the data inputs and the methodological choices. To avoid these challenges, in this study we use the EU KLEMS database for the national and industry level analysis, and move even deeper to look into firm level data across Europe.25 Considering macroeconomic data, the EU KLEMS source has prioritized a common industrial classification and consistent definitions for various types of capital and labor combined with the use of similar price concepts for inputs and outputs. We use a growth accounting framework to assess the contribution of various inputs to aggregate growth (See Appendix 1 for more details).26 From the analysis we can measure two different effects on productivity and value added by industry: the embodied technological change as measured by the ICT and non ICT capital inputs; and the disembodied technological change as measured by the total factor productivity (TFP) component. The former is a measure of the tangible technology impacts realized by the purchases and installations of new systems and machines that help automate manual processes or speed up existing ones. The latter is a measure of the intangible gains 24
R Inklaar et al., "Productivity and Competitiveness in the EU and the US," in EU Productivity and Competitiveness: An Industry Perspective. Can Europe Resume the Catching-­‐up Process?, ed. M O'Mahony and B van Ark (Luxembourg: Office for Official Publications of the European Communities, 2004). 25
http://www.euklems.net/ 26
D W Jorgenson and Z Griliches, "The Explanation of Productivity Change," Review of Economic Studies 34, no. 3 (1967); Jorgenson et al., "Industry Origins of the US Productivity Resurgence." 10 deriving from the use of technologies but not limited to that. TFP encapsulates the added effects that can be realized over and above the tangible technological inputs ranging from organizational restructuring, management practices, regulatory redesign and institutional adaptation. In this report, we use the findings from TFP in two ways: the positive findings are attributed to reactive governance at the national level aiming to facilitate new technology capabilities; in contrast the negative findings are attributed to regulatory, cultural and institutional inertia that fails to realize the “expected” gains from measureable ICT and non-­‐ICT inputs. Put simply, a new technology system can improve a standard process by x% across firms, industries and countries; when we find cases of lower and higher effects from this specific change we interpret them as positive or negative productivity gains. The literature is also supportive of this view suggesting that TFP can also be negative as a short-­‐term effect of organizational restructuring or herd behavior. 27, 28 Thus we use comparable industry level data from EU KLEMS across European countries to measure the following ICT impacts: • Percentage impact attributed to ICT capital (embodied technological change); • Percentage impact attributed to TFP (disembodied technological change). 2.1.2 Results Figure 2.1 below presents the overall ICT capital and TFP gains by country for the period 1996-­‐2010. There is a generally strong effect from increased investments in the so-­‐called embodied technological change that materializes from capabilities built in the new technologies. Figure 2.1: ICT capital & Total Factor Productivity (TFP) impact in % value added (1996-­‐2010) 29 27
M O'Mahony and M P Timmer, "Output, Input and Productivity Measures at the Industry Level: The EU Klems Database," The Economic Journal 119, no. 538 (2009)., 28
Growth accounting assumes d.costs/dt=d.rev/dt; one typical example of herd behavior was during the “dot-­‐
com” bubble. 29
ICT capital contribution for the US is estimated at 50% of all capital contribution. 11 The UK and Spain seem to have the highest returns from the capital deepening while France and Italy seem to lag in this process. Turning to the total factor productivity gains we are faced with a different picture: Sweden, Finland and Germany are the clear leaders and realize the full potential of both ICT and non-­‐ICT investments. In contrast, Italy and Spain manifest a systemic inertia and fail to make the most of these investments. In fact we see that the value added at the country level is negative suggesting that technology investments may have been misguided (through, perhaps, herding effects) or that institutional and managerial capacities have failed to capitalize on the new technologies. This is a very crucial period of expansion and growth for the majority of European countries and we can clearly identify some signs that may have led to the catastrophic consequences of the recent recession. Figure 2.2 below presents the analysis for more recent years (2005-­‐2010). Here we see that whereas all countries have much smaller but still positive effects from ICT capital deepening during the recession, Spain and Italy have been hit the most in terms of output and TFP gains. Finland, Netherlands and the UK have much smaller effects from this downturn while Germany and Sweden report smaller positive growth rates. Figure 2.2: ICT capital & TFP impact in % value added (2005-­‐2010)30 It is important to understand how well the European countries have performed over the same period compared to other global competitors. As such, we included in our sample data from the US and Japan for the same metrics. Interestingly, most of the European countries have performed better than Japan and very close to the US in terms of total factor productivity for the earlier period, catching up some of the wide productivity gap in the pre-­‐1995 times. Italy and Spain did not follow that trend in this period. These effects vanished during the first years of the recession for all countries in this sample. This country level analysis can be considered within the broader context of understanding the impact of ICT and the contribution of resources and governance in creating value. As expected, countries with higher incomes, educational attainment, research centers and universities combined with a higher quality of institutions have managed to make the most of new technologies and go through the recent recession quickly without major shocks. The success of the existing “model” is embedded in institutional quality that takes time to build and the increased margins industry leaders 30
ICT capital contribution for the US is estimated at 50% of all capital contribution. 12 earn from the production and supply of high quality goods and services. As long as socioeconomic conditions allow EU nations – and large cities within them – to attract and retain talented individuals and global capital, this “model” will be difficult to copy by competing countries. It is also worth mentioning that, with the exception of Germany, countries within the common currency have generally fared worse than non-­‐Eurozone members. While there is no causal link in our data, this trend suggests that connecting otherwise different institutional systems is far from a panacea for the unification of nations and may also have mixed impacts for their output and export capabilities. 2.2 Industry Analysis The national difference between the impacts of ICT on EU and US productivity can also be identified at the industry level. In particular, the manufacturing and service industries for 12 EU countries and the US between 1980-­‐2000 experienced similar real investment and capital service flows across regions. 31 However the shares of ICT in total investment and capital service flows in the EU were approximately half to two thirds of the U.S. level throughout the period. Furthermore, in relative terms ICT capital in the EU was about half of the U.S. contribution to labor productivity growth up to the mid-­‐1990s, and since then the relative contribution of ICT capital improved, but overall EU productivity growth collapsed. In a wider industry analysis of European (France, Germany, Netherlands and UK) and US industries from 1987–2004, it was shown that the lower ICT contribution to EU growth continued throughout the early 2000s with strong labor productivity gains in US ICT-­‐using sectors.32 In this part we further analyze ICT capital and productivity impact. The focus here is the sectoral composition and industries in each of the European countries analyzed with the same EU KLEMS data. We examine the industries that have experienced significant ICT capital deepening and high total factor productivity over the period 1996-­‐2010. First we identify the industries where ICT investments were associated with substantial changes in output, focusing on the leading industries in terms of average annual value added over the study period (1996-­‐2010).33 Figure 2.3: Industries benefiting from ICT investments (1996-­‐2010) 31
B van Ark et al., "ICT Investments and Growth Accounts for the European Union," in Groningen Research Memorandum (Groningen, NL: Groningen Growth and Development Centre, 2002). 32
B van Ark and R Inklaar, "Catching up or Getting Stuck? Europe's Troubles in Exploit ICT's Productivity Potential,"ibid. (2005)., van Ark, O'Mahony, and Timmer, "The Productivity Gap between Europe and the United States: Trends and Causes." 33
Industries with more than 1% value added from ICT capital per year. 13 Figure 2.3 above presents the analysis of the industries benefiting from ICT investments. Clearly the ICT-­‐producing industries lead in this ranking with telecommunications, IT and other related services capturing the first two positions. Financial and insurance services come third indicating the dramatic effects new computing facilities and real time communications have for this – ICT-­‐using – sector. Other affected industries include logistics (or “postal and courier activities”), services and processing (“professional, scientific, administrative and support”), media and publishing (“publishing, audio-­‐
visual and broadcasting”) and “electrical and optical equipment”. These are also partly linked to the core ICT industries and it is expected that increased investments will improve their output and business processes.34 Using the same cross-­‐sections for this period, it is possible to focus on the countries that had the most impacted industries. From the analysis it is clear that the UK – by a large margin – is the leading country followed by the Finland, Netherlands and Spain. What is also reflected from the national data is that the has UK focused – perhaps excessively – in the capital deepening effects of ICT in return for this added output when compared to other countries (Sweden and Finland) that combined these investments with substantial organizational changes, reflecting substantial benefits from higher productivity. To investigate this last point, we examine the contribution of TFP to value added growth.35 Figure 2.4 below presents these results. ICT-­‐producing and ICT-­‐using industries reap the benefits from increased TFP growth. In fact their lead is higher almost by an order of magnitude compared to the rest of the industries. 34
A number of sectors have been disrupted by the introduction of ICTs and have not necessarily benefited or reported increased output and performance. Instead some of these industries that failed to adapt disappeared or were severely hit (analogue photography, music industry, high-­‐street retail, and others). 35
An average annual contribution higher than 3% per year. 14 Figure 2.4: Industries benefiting from ICT productivity gains (1996-­‐2010) Nevertheless the range of sectors and countries where spillover effects are identified is remarkable: petroleum and petrochemicals, wholesale and retail trade, agriculture, machinery, textiles, financial services, transport equipment and others appear in this mix. Grouping this information by country we clearly see that Sweden, Finland and to a lesser extend Germany have experienced productivity growth over and above the EU average. In fact, Sweden and Finland have been global leaders for the period (1995-­‐2010) surpassing the US and Japan in productivity gains. In the post-­‐2005 period only Sweden maintained its lead above the US. The slower adopting countries like France, Italy and Spain appear to have substantial benefits for their ICT-­‐producing sectors only (telecommunications) whereas these countries have also excessively invested in ICT without getting back comparable returns to the rest of the EU. Combining these findings we identify different patterns across European countries in terms of value added perhaps pertaining to their sectoral composition and industry mix. For example, a stronger impact from ICT capital investments appears in countries with a focus on finance and insurance industries like the UK and Netherlands. These ICT-­‐using sectors benefit from improved computing facilities and communication services while their relative productivity gains, including management and organizational restructuring seems limited. On the other hand, countries with a high-­‐technology and heavy manufacturing focus ranging from electronics, machinery, chemicals, petroleum and textiles appear to benefit from substantial productivity gains deriving from both ICT and non-­‐ICT investments. These manufacturing-­‐intensive countries include Germany, Sweden and Finland. France has a less pronounced ICT investment focus and average productivity gains from ICT-­‐
producing industries only. Southern European countries seem to have low returns on ICT capital investments and negligible productivity gains from ICT-­‐using sectors. The implications of these findings are further explored in section 3.3 where we look into the commercialization trends of ICT innovation across EU countries and combine their progress during the past decades with recent evidence. 15 3.0
INNOVATION IMPACT OF ICT This section considers the implications of ICT creation through firm research and development (R&D), patenting and commercialization of innovation through venture capital-­‐funded firms. We also investigate the rates of ICT innovation and consider firm-­‐level R&D, patents and venture capital investments (VC). 3.1 ICT Innovation in firms 3.1.1 ICT-­‐using firms Research attention in recent years has shifted from national and industry levels, to firm level data. Most studies in the US, EU or elsewhere reveal a positive and significant association of ICT with productivity.36 A feature of these studies is that they suggest that the effect of ICT investment on firm performance is greater than might be expected from the standard neoclassical assumptions underlying the growth accounting frameworks.37 This means that firms that invested more in computers produced more output per unit of input echoing increasing returns to ICT investments.38 One of the main reasons put forward for the outsized returns of ICT capital is the presence of complementary organizational capital.39 That is, the measures of ICT used in these earlier studies may be capturing the effect of ICT as well as other complementary inputs such as organizational structures and efficient management practices, typified by employee control over task allocation and the pace of work and greater teamwork.40 In fact there is evidence suggesting that complements such as ICT, organization and skills significantly and positively co-­‐vary.41 Because of these complementarities key firm-­‐level organizational characteristics are correlated with ICT capital but not with physical capital. More specifically, firms with ICT investments and good organizational practices appear to have the highest market value.42 This is manifested in the case of multinationals operating in the same region. For example the returns are much higher for US multinationals operating in Europe compared to non-­‐multinationals statistically similar establishments. These effects are attributed to the interaction between ICT and organizational aspects, such as people management through promotions, hiring, firing, and reward systems.43 36
B Lehr and F Lichtenberg, "Information Technology and Its Impact on Firm-­‐Level Productivity: Evidence from Govermment and Private Data Sources," Canadian Journal of Economics 32, no. 2 (1999)., E Brynjolfsson and L M Hitt, "Computing Productivity: Firm-­‐Level Evidence," Review of Economics and Statistics 85, no. 4 (2003)., J Forth and G Mason, "The Persisence of Skill Deficiencies across Sectors, 1999-­‐2001," in Employers Skill Survey: New Analyses and Lessons Learned, ed. G Mason and R Wilson (Nottingham, UK: Department for Education and Skills, 2003)., N Bloom et al., "It Productivity, Spillovers and Investment: Evidence from a Panel of UK Firms," (London, UK: Enterprise LSE, 2005)., N Bloom, R Sadun, and J Van Reenen, "American Do It Better: US Multinationals and the Productivity Miracle," American Economic Review 102, no. 1 (2012). 37
Van Reenen et al., "The Economic Impact of ICT." 38
Brynjolfsson and Hitt, "Computing Productivity: Firm-­‐Level Evidence." 39
Van Reenen et al., "The Economic Impact of ICT."; Bloom, Sadun, and Van Reenen, "American Do IT Better: US Multinationals and the Productivity Miracle." 40
E Brynjolfsson, L M Hitt, and S Yang, "Intangible Assets: Computers and Organizational Capital," Brookings Papers on Economic Activity 1 (2002). 41
T F Bresnahan, E Brynjolfsson, and L M Hitt, "Information Technology, Workplace Organization, and the Demand for Skilled Labor: Firm-­‐Level Evidence," Quarterly Journal of Economics 117, no. 1 (2002). 42
Brynjolfsson, Hitt, and Yang, "Intangible Assets: Computers and Organizational Capital." 43
Bloom, Sadun, and Van Reenen, "American Do It Better: US Multinationals and the Productivity Miracle", N Bloom and J Van Reenen, "Measuring and Explaining Management Practices across Firms and Nations," Quarterly Journal of Economics 122, no. 4 (2007). 16 Looking more specifically at intra-­‐EU variability, studies have found a significant effect of ICT on manufacturing but not on services in Germany, a weakly significant effect of ICT in Italy, and a significant impact of PCs/worker in the service sector for the UK.44 Although these studies have considered the effect of ICT on firm performance, they have not considered the comparison between those firms that are intensive users of ICT, and those that are not. As such we focus our analyses on comparisons between ICT-­‐intensive and non-­‐ICT intensive firms. 3.1.2 Research leading to innovation in firms R&D is the main driver of ICT innovation in firms. Some scholars have measured the importance of research expenditures as a separate input of production functions contributing to the overall output of the industry or firm.45 There is evidence of a positive link between the amount of basic research carried out by a firm and its rate of increase of total factor productivity, when its expenditures on applied R&D are held constant.46 Clearly these metrics are prone to numerous biases like reporting, changing tax regimes or other idiosyncratic firm-­‐level effects. More recently measures of intangible assets and other innovation indicators have been used in a range of knowledge production functions. Here, R&D expenditures are primarily an input indicator of the efforts that firms make in establishing knowledge that might eventually lead to outputs. These studies have usually estimated research returns through patent counts and patent applications, with some correlating R&D input with R&D output using patenting activity.47, 48 In general a positive correlation between R&D and patent applications has been observed.49 Looking into other innovation counts, it has been shown that R&D is positively correlated with all indicators of innovation output including process innovation, product innovations new to the firm or market, shares in new product sales and patent-­‐protected sales.50 Nevertheless, basic research does not necessarily directly influence innovation performance on its own. The early view of the impact of R&D on innovation has come from a Schumpeterian perspective, which assumes a linear process of innovation with R&D as a necessary first step for firm-­‐level innovation and asserts a positive link between firm size or monopoly power and innovative activity.51 In this context large firms may be in a better position to carry out the R&D necessary and to exploit the market potential of each innovation. However the impact of R&D on 44
T Hempell, "What's Spurious, What's Real? Measuring the Productivity Impacts of ICT at the Firm-­‐Level," Empirical Economics 30, no. 2 (2005), N. Matteucci et al., "Productivity, Workplace Performance and ICT: Industry and Firm-­‐Level Evidence for Europe and the US," Scottish Journal of Political Economy 52, no. 3 (2005). 45
J Mairesse and P Mohnen, "The Importance of R&D for Innovation: A Reassessment Using French Survey Data," Journal of Technology Transfer 30, no. 1-­‐2 (2005); E Mansfield, "Rates of Return from Industrial Research and Development," American Economic Review 55, no. 1/2 (1965). 46
"Basic Research and Productivity Increase in Manufacturing," American Economic Review 70, no. 5 (1980). 47
J Hagedoorn and M Cloodt, "Measuring Innovative Performance: Is There an Advantage Using Multiple Indicators?," Research Policy 32, no. 8 (2003). 48
Z Griliches, R&D and Productivity: The Econometric Evidence (Chicago, IL: The University of Chicago Press, 1998); "Patent Statistics as Economic Indicators: A Survey," Journal of Economic Literature 28 (1990); J Hausman, B H Hall, and Z Griliches, "Econometric Models for Count Data with an Application to the Patents-­‐
R&D Relationship," Econometrica 52, no. 4 (1984). 49
I Prodan, "Influence of Research and Development Expenditures on Number of Patent Applications: Selected Case Studies in Oecd Countries and Central Europe, 1981-­‐2001," Applied Econometrics and International Development 5, no. 4 (2005). 50
Mairesse and Mohnen, "The Importance of R&D for Innovation: A Reassessment Using French Survey Data.", 51
J A Schumpeter, Capitalism, Socialism and Democracy (London: Routledge, 1943).. 17 innovation performance is influenced by other factors too.52 For example, some studies have found that small US firms (defined as less than 500 employees) tend to be more innovation intensive than large firms,53 while other studies have found that innovation performance is more correlated to R&D than to firm size.54 Tax credits and subsidies have also been central in the industrial policy debate suggesting that R&D credits lead to additional innovation output.55 The importance of R&D investments on GDP growth is also substantial. An R&D subsidy awarded to either entrants or incumbents (larger firms) that is equivalent to 1% of GDP increases the growth rate of the economy by about 0.13% and welfare by 1.5-­‐2% in consumption equivalent terms. However, “survival” or non-­‐
R&D subsidies for the continued operation of incumbents of the same magnitude has a large negative effect, reducing the growth rate by about 0.27% and welfare by 4.3% in consumption equivalent terms.56 So far there is little evidence related to the role of R&D in innovation in ICT and non-­‐ICT industries. As such below we investigate the effect of R&D on innovation in European firms. 3.1.3 Firm level analysis Firm analyses have significant advantages over industry or national levels. At the micro level it is easier to identify management practices and skills that do not necessarily span across businesses and to examine more detailed characteristics linked to year on year performance, investments in research and development, and employment metrics. We examine an extensive group of millions of European firms and select a sample of 23,451 that report R&D activity in the past 4 years.57 Our source for this information is the Orbis/Amadeus dataset. Within this sample there are 736 ICT firms reporting R&D expenditure that we use as the treatment group in this analysis. Labeling a firm as ICT or non-­‐ICT is not as straightforward as it used to be. There are various firms that may have substantial ICT departments that do not produce or offer ICT products and services, and others with a diverse internal structure under the ICT umbrella. As such, we expand the ICT definition to include firms that operate in the broader ICT sector even if these are classified under different industry classifications (e.g., manufacturing, Siemens).58 This helps us broaden our treatment group reaching approximately 10% of the entire sample (2,333 ICT firms) with the expanded definition. After separating ICT and non-­‐ICT firms we analyze the patterns in each group by country, firm age, size and operational revenue. Figure 3.1 below presents a comparison of R&D investment between ICT and non-­‐ICT firms. This figure demonstrates that overall non-­‐ICT firms have been spending 2.6 million EUR more per firm on R&D compared to ICT firms in 2012. Across countries this gap differs vastly: ICT firms in Sweden 52
M Dodgson, D M Gann, and A J Salter, The Management of Technological Innovation (Oxford, UK: Oxford University Press, 2008). 53
Z J Acs and D B Audretsch, "Innovation in Large and Small Firms: An Empirical Analysis," American Economic Review 78, no. 4 (1988). 54
Mairesse and Mohnen, "The Importance of R&D for Innovation: A Reassessment Using French Survey Data." 55
D Czarnitzki, P Hanel, and J M Rosa, "Evaluating the Impact of R&D Tax Credits on Innovation: A Microeconomic Study on Canadian Firms," Research Policy 40, no. 2 (2011). 56
Acemoglu, D., Akcigit, U., Bloom, N., & Kerr, W. R. (2013). Innovation, reallocation and growth (No. w18993). National Bureau of Economic Research. 57
The pharmaceutical firms are excluded from the sample due to their large investments in R&D, which might be mostly non-­‐ICT related. 58
We use the following pattern matching looking into firm descriptions and manually check the firms included in this selection: communication, telecommunication, electronics, information, ICT. 18 spend three times more than non-­‐ICT ones; similarly ICT firms in Germany (63%) and the UK (67%) spend more than non-­‐ICT firms. In contrast, non-­‐ICT firms in France, Belgium and Switzerland report more than twice the R&D expenditure of local ICT firms. Moreover there is vast heterogeneity in this metric as it includes entities that range from startups with less than 10 employees to established firms with billions EUR revenues. Figure 3.1: R&D investment per ICT/non-­‐ICT firm Figure 3.2 below presents the analysis of ICT spending by firm age. This demonstrates that the gap is most pronounced in the comparison of the investments in R&D of old and large non-­‐ICT firms (like pharmaceuticals). However, young ICT firms are responsible for one quarter of all ICT R&D investments in Europe. This is not the case of non-­‐ICT firms where more than half of the R&D activity is undertaken by older firms. Figure 3.2: Who spends in R&D? Older firms in non-­‐ICT sectors (2013) Adding up all the R&D per year for ICT and non-­‐ICT sectors we identify clear scale effects for the larger countries (Germany, France and the UK) and with Sweden as a consistent leader in R&D 19 investments across sectors.59 In our sample, approximately 155 billion Euros were invested in R&D in 2012 across all companies. ICT innovation leaders in Europe include the UK and Germany with approximately 7.5 billion EUR invested in R&D per year in 2012. Sweden follows with 4.2 billion EUR and France almost reaches 1.8 billion EUR. Given that Germany has almost 8 times the population of Sweden the level of R&D intensity in Sweden is impressive. Investigating the link between firm age (or maturity) and R&D innovation, we observe that older firms generally spend more for basic research. This effect may be confounded with the higher revenues and employee counts that often come with established firms. Younger ICT firms spend substantially more than non-­‐ICT ones while this trend is reversed for firms between 10 and 29 years in the market. The effects of the recent recession may be linked to lower investments in new firms during 2012, which is generally not seen for more mature players. Research expenditure increases with employment as larger firms spend more and ICT firms are more dynamic across all age groups. Similarly research investments and revenue are positively linked with the exception of some very small ICT firms. 3.1.4 R&D Intensity While all these angles point to the expected scale effects (age, revenue, employment) we further look into the R&D intensity for these metrics – the R&D invested per EUR of revenue. This way we can test – controlling for scale – which firms actually drive the research and innovation in the sectors of interest. Figure 3.3 below presents an analysis of the R&D spend of young and small firms in 2013. Here, for revenue intensity the previous trends are reversed: smaller firms spend much more on R&D than larger ones per EUR of sales revenue. Young (<10 years) and small (<100 employees) firms spend 10 times more than old and small firms and 100 times more than large firms in R&D per employee. Figure 3.3: Young and small firms spend orders of magnitude more money per million Euros of revenue compared to other clusters (2013) 59
We have limited information for Finland in the Amadeus sample. 20 Looking further into R&D intensities for ICT and non-­‐ICT firms, we observe that small ICT firms lead in terms of revenue intensity. We combine these results with the overall expenditure across the EU economy: while young and small firms investing in research are a small fraction of all R&D for the non-­‐ICT sectors they represent more than 25% for the ICT (see Figure 3.2). Therefore we depart from the traditional industrial policy arguments in support of SMEs and suggest that young and small ICT firms exhibit a disproportionately large impact on innovation vis-­‐a-­‐vis their size and experience. Given their intensity in creating these innovations, ICT startups are pivotal for the creation of new technologies and services. The success of these startups and their impact on the economy is discussed extensively in subsequent sections. 3.2 Patents Patents have fascinated economists as they appear to offer a mechanism of understanding such influences as the “underlying” rate of technical and scientific progress.60 A patent is a document, issued by an authorized governmental agency, which grants the right to exclude anyone else from the production or use of a specific new device, apparatus, or process for a stated number of years. Patents are awarded when the new device, apparatus or process is novel, non-­‐obvious, and useful. Patents can be considered a measure of inventive activity in that they represent a “minimal quantum of invention” that can be observed and statistically analyzed. Put differently, patents can be used as the primary, observable output indicator of a firm’s (or individual’s) knowledge production.61 Patents act in many ways: first, by incentivizing innovation through exclusivity of commercial exploitation; second, by identifying the local institutions as the gatekeepers of this process; and third, by being a tradable right they can be exploited by their – often reassigned – owners and not only their inventors. In other words, patents underpin a market for technology. While the mechanisms and granting channels have been an issue of debate for more than two millennia, few can object that patents reflect some important aspects of the intellectual capital produced in a region at a given time.62 In this context we use the patent activity in ICT sectors to assess the strengths of each region in Europe and compare them in a global market. Patents are not the only form of intellectual property protection – copyrights for example are excluded in our analysis – but they also represent a measure of innovation. The use of patents to investigate the impact of ICT on firm performance has generally been conducted at the firm level. Early works investigated the correlation between firm patent counts and innovation performance63 and showed that the ownership of highly cited – or innovative – patents contributes to the market value of the firm that holds these patents.64 The role of ICTs in patent 60
Z Griliches, "Patents as Economic Indicators: A Survey," Journal of Economic Literature 28, no. 4 (1990). L Kleis et al., "Information Technology and Intangible Output: The Impact of It Investment on Innovation Productivity," Information Systems Research 23, no. 1 (2012); B H Hall, A B Jaffe, and M Trajtenberg, "Market Value and Patent Citations," RAND Journal of Economics 36, no. 1 (2005). 62
The first recorded evidence of intellectual property protection dates back to ancient Greece (500 BC) when chefs were granted year-­‐long licenses for creating particular culinary delights. (Stanford Encyclopedia of Philosophy: http://plato.stanford.edu/entries/intellectual-­‐property/) 63
Z Griliches, R&D, Patents and Productivity (Chicago, IL: University of Chicago Press, 1984). 64
Hall, Jaffe, and Trajtenberg, "Market Value and Patent Citations." 61
21 output has been found to range from a direct input to patent grants,65 to a tool for product and process innovation not necessarily codified by formal intellectual property rights.66 Echoing these approaches, the patent count of a particular ICT-­‐producing or ICT-­‐using industry can be used to compare the performance of different countries or regions. To do so, it is necessary to assume that the process required for a patent in a particular industry is common in all countries. This assumption is not too strong, given that many countries have patent processes that comply with "world patent applications" made under the Patent Cooperation Treaty (PCT). This allows us to identify those countries that are leaders and specialists in particular industries over time and across regions. As innovations vary enormously in their technological and economic "importance" or "value”, and that the distribution of such "values" is extremely skewed, simple patent counts are inherently limited in the extent to which they can capture such heterogeneity.67 Furthermore, given the strictness of criteria for a patent, it is possible to compare the patenting process across countries. In particular, patents go through a pending period before they are granted, and the differences between these may enable insights into the effects of scale and bureaucracy of differing patent offices. Again, the assumption here is that the process required for a patent in a particular industry is common across countries and offices. 3.2.2 EU research specialization and leadership For the analysis we use OECD data for patent applications and grants in three main ICT patent classes: G (physics) and H (electricity) and B (operations).68 We use a subset of these IPC classes for core and adjacent IPC classes following earlier works in the field.69 In each of the classes we identify specialist and leader countries. The following definitions are used in the patent analysis. •
Specialist: the country with the highest percent of patents in each patent office for a specific sub-­‐class (sub-­‐class patents/ total patents) •
Leader: the country with the highest number of patents in each patent office for the sub-­‐
class (sub-­‐class patents) We look at patents granted from the EPO and USPTO and patent applications at the EPO and PCT (“international” applications under the patent cooperation treaty indicating the EPO as the regional office), and compare them at the EU28 and World level. All tables with sub-­‐class descriptions, codes, and specialist and leader countries are included in Appendix 2. The results (see Appendix 2) show that there is no EU country leading the USPTO globally, however there is potential for leadership based upon specialization. Although the EU28 leader, Germany is mostly outrun by Japan or the USA in the global lead without accounting for scale effects in favor of larger countries. Interestingly, EU28 specialists maintain leadership positions even in global comparisons in 61 cases out of 70. 65
Kleis et al., "Information Technology and Intangible Output: The Impact of It Investment on Innovation Productivity." 66
Van Reenen et al., "The Economic Impact of ICT." 67
Hall, Jaffe, and Trajtenberg, "Market Value and Patent Citations."; Z Griliches, A Pakes, and B H Hall, "The Value of Patents as Indicators of Inventive Activity," in Economic Policy and Technological Performance, ed. P Dasgupta and P Stoneman (New York, NY: Cambridge University Press, 1987). 68
The list of the classes is shown in Appendix 2. 69
Kim and Hwang, 2012: A Study on the Identification of Cutting-­‐Edge ICT-­‐Based Converging Technologies. 22 Netherlands is particularly strong in semiconductor printing; Belgium in optical elements, image data processing and semiconductor devices; Finland in telephonic communications, data transmission innovations, measuring electric and magnetic variables, digital data processing and signaling systems; Austria in data recognition and presentation and electrical components assemblages; Hungary in radio direction processes, data processing, data transmission and electric discharge equipment; Italy in multiplex communications, static storage devices and electric discharge equipment; Spain in data recognition and transmission and coupling devices. The breadth of ICT specialization in Europe is remarkable and comparable to no other region in the world. The exploitation of these specializations seems to diverge from the substantial innovation policy efforts within Europe. The relationship between specializations across patent offices leads to some interesting recommendations. For example firms, research centers and universities from Finland and Belgium could be incentivized to collaborate in the fields of telephonic communications (H04M) to improve their regional and global positions. Similarly Hungary and Finland could work together in electronic data processing, Austria and Spain in data recognition, Italy and Hungary in electronic discharge equipment, Spain and Germany in electrically conductive connections and Spain with Finland in data transmission. This would require a fine-­‐grained analysis of the entities and researchers capable to contribute in those fields and prioritization of specific research areas for further exploitation. Looking into patent applications we can further fine-­‐tune these recommendations and combine the “trending” sectors across countries with the established critical mass of specialization. In this context Hungary should work with Netherlands and Finland in radio navigation innovations; France with Austria and Spain in data recognition; Netherlands, Finland and Italy in processes that improve electric and magnetic measuring. Additionally some clear specializations should be prioritized at the national level. For example, ICT innovations related to the development of solid state devices in Belgium, electrical component manufacturing in Austria, control/regulating systems, circuits for electric power and electrical connections in Germany and electric data processing in Finland identify some regional champions. Delving deeper into the specialization potential of EU countries vis-­‐a-­‐vis their global counterparts, we have computed a ratio (R) of the number of patents for each EU28 leader and specialist to the number of patents of each global leader and specialist.70 The greater the ratio, the smaller the difference between the number of patents of EU and World leader (or specialist) for a particular sub-­‐
class. A ratio of 1 translates into a global leadership of the EU28 country. Based on these calculations we can identify the promising areas for research where European countries are close to the global lead in the specific patent class. Overall, EU specialists maintain the leading positions in most ICT related classes. This is particularly important for strengthening these regions to maintain and expand their reach. Looking into the leaders category we find that Germany is very close to the US in “measuring and testing” (G01R),71 in “basic electric elements” classes (H01J, H01R), and “electric techniques” (H05K).72 3.2.2 ICT innovation spillovers Our focus on ICT innovations stems from the intuition that ICTs are a general-­‐purpose technology. In this case the innovation spillovers from each ICT patent spread both within and across sectors and industries. To test this hypothesis we use the most comprehensive dataset available from the 70
The ratio is between 0 and 1. EPO granted and applications. 72
EPO granted and applications. 71
23 European Patent Office (PatStat) to compute the number of citations by technology field. More than 78 million patent applications and 45 million patent families are included in this analysis. In this exercise we look into patent families to discount identical innovations being applied in different patent offices or countries. Figure 3.4 below presents the analysis of citations per patent family and technology sector. Considering the average citations per patent family for each technology we find that computer technology, semiconductors, surface technology, digital communications, optics, telecommunications all populate six of the top ten most cited patent families across 37 sectors. Figure 3.4: Citations per patent family and technology sector The next step in this analysis looks into the origins of innovators across European countries and compares it with the US and Japan. With this analysis we want to identify if there is an innovation deficit in the region and to portray the capabilities in direct comparison with other global champions. This analysis complements the previous findings from the leader/specialist scores as it allows us to position each country in a broader technology field that encapsulates adjacent IPC classes. Moreover this dataset comes from a different source (PatStat, EPO) allowing us to check again the validity of the previous findings. 24 Figure 3.5: Percent of global patents by technology field and country Figure 3.5 above presents an analysis of global patenting activity by technology field and EU country. Accounting for the population of each country, Finland leads the digital communications sector followed by Sweden. Relaxing these controls we find that after the US and Japan, Germany maintains its leading EU position followed by Finland, Sweden, France and the UK.73 A very similar distribution is found in telecommunications too. In computer technologies the US is the global leader followed by Japan and the EU; once population controls are included Finland comes very close to the top. Germany does extremely well in nanotechnologies and microstructures, surface technologies and coating, measurement, control and electrical machinery. Sweden is top at medical and nanotechnologies. France has some competencies across sectors – telecommunications, computer technology and digital communications – but is nowhere near the leaders. Spain and Italy score poorly across the board, with or without population controls. However, patents do not represent all IP activity in a region and some R&D is not patentable in Europe (more notably software) while the long application process may deter innovators to follow this route. Nevertheless patents are legal rights with a term period of 20 years (after the application date) thus representing strong monopolies for firms and individuals to capitalize on their research outputs. As such we will expand our analysis in the following sections to evaluate the degree of commercialization of these patents across countries through venture capital and startup activities. 3.3 Venture Capital The globalization of capital markets and the increased competition for the development of innovative ideas has gradually transformed the incubation process of high technology startups into an art of its own. Before continuing, we make two crude observations. First, the realization that a small fraction of new firms is responsible for almost all growth in a region has lead entrepreneurial policies in the last decades to focus into “growth entrepreneurship”. The numbers are startling: of all new firms the top (quality) 5% generates 74% of all growth and the top 1% accounts for 53%.74 Second, a better understanding of the other 95% of startups (or simply new small businesses) is 73
PatStat (2014). Guzman, J., & Stern, S. (2014). Nowcasting High Growth Entrepreneurship-­‐A Methodology using Public Records, with updated numbers from http://ilp.mit.edu/images/conferences/2014/machine/presentations/Stern.2014.2MA.pdf 74
25 crucial too. Looking into business registration data it is clear that very few of them intend to bring a new idea to the market. Instead replication of existing services in an existing market is the primary focus of most new small businesses with their desire to grow big or innovate being very limited.75 Keeping these observations in mind, we delve into the dynamics of innovative startup incubation in Europe and other areas around the world. In order to compete in the tech startup market, aspiring entrepreneurs need to be trained and funded. To build a successful high growth entrepreneurship ecosystem one needs a flow (supply) of new ideas – from universities, research centers and other businesses in the region; an network of experienced finance professionals, engineers and communicators; and a global reach to other innovation hubs. Having a successful ecosystem used to be a privilege of Silicon Valley, but orchestrated efforts across other US states and countries has created a healthy flow of projects in entrepreneurship ecosystems in half a dozen of cities across the world.76 Venture capital (VC) is the financial underpinning of high growth startups, often inaccurately termed as a separate asset class. In this section we compare the non-­‐commercialized R&D output in each country (patents) and the level of ICT and non-­‐ICT exploitation (as measured by VC). We compare European countries with the USA and try to identify some key parameters that catalyze the returns of mature research output. We also note that, even if the process of selecting technology champions may not be objective, there is no obvious harm from spending private funds to help grow a promising firm. In fact the benefits for a region that organizes these activities can be both direct and indirect. 3.3.1 Background VC is considered to be the most appropriate form of financing for innovative firms in high-­‐tech sectors. In the past decade the European VC market lagged behind its US counterpart and had a limited effect to raise equity capital, grow, and create jobs.77 Moreover, the bank-­‐based systems in Continental Europe have been viewed as less capable of financing innovation and of facilitating path-­‐
breaking innovations than the market-­‐driven systems in the US and the UK.78 As a consequence there has been concerted effort on behalf of European governments to develop high growth entrepreneurship ecosystems and support disruptive innovation.79 The EU Commission startup Europe initiative has been set up to support these actions.80 To date one quarter of all accelerators schemes are present in Europe, and almost 20% of companies funded have graduated from European accelerators while 73% of all “graduate” companies are located in USA. Although these policy undertakings are still a work in progress, there has been much academic work on the effects of VC on firm performance. Some studies have identified a positive link between VC funding, innovation,81 and performance,82 while others have shown that innovator firms are more 75
Hurst, E., & Pugsley, B. W. (2011). What do small businesses do? (No. w17041). National Bureau of Economic Research. 76
More than 1 billion USD of VC in 2014 (TechCrunch) – Figure 3.8. 77
L Bottazzi and M Da Rin, "Venture Capital in Europe and the Financing of Innovative Companies," Economic Policy 17, no. 34 (2002). 78
see for instance A W A Boot and A V Thakor, "Banking Scope and Financial Innovation," Review of Financial Studies 10, no. 4 (1997); R Rajan and L Zingales, "Financial Systems, Industrial Structure, and Growth," Oxford Review of Economic Policy 17, no. 4 (2001); W Carlin and C M Mayer, "Finance, Investment and Growth," Journal of Financial Economics 69, no. 1 (2002). 79
A P Faria and N Barbosa, "Does Venture Capital Really Foster Innovation?," Economics Letters 122, no. 2 (2014), European Commission, "Cross-­‐Border Venture Capital in the European Union," (Brussles, Belgium2009). 80
http://ec.europa.eu/digital-­‐agenda/open-­‐disruptive-­‐innovation-­‐0 81
Faria and Barbosa, "Does Venture Capital Really Foster Innovation?." 26 likely to receive funding than imitators.83 Increases in VC activity in an industry are associated with significantly higher patenting rates too,84 while in Europe VC has helped innovative firms to reach IPOs in European stock markets.85 Over the period 1991-­‐2005, VC has accounted for more than 10% of industrial innovation in Europe, and its success was mostly concentrated in countries with lower barriers to entrepreneurship, with a tax and regulatory environment that welcomes venture capital investment, and with lower taxes on capital gains.86 In spite of these effects there is a growing strand of literature suggesting that causality runs from patents to VC, or put another way, that innovation creates a demand for VC and not VC a supply of innovation.87 High technology firms backed by VC are likely to outperform their non-­‐VC-­‐backed counterparts,88 due to the active monitoring and coaching that VC firms undertake to their portfolio companies,89 and the signal of quality that VC investment conveys.90 However these effects mostly affect firm growth,91 and not profitability once more robust controls are in place.92 Firm age is also important in determining the impact of VC funding on innovation. In particular, the performance effects are reduced when the funded firms are very young or mature,93 with a performance peak identified at later business stages.94 The pivotal role of VC in firm productivity has been tested through comparisons of portfolio firms' productivity growth before and after the first VC round. While productivity growth is not significantly different between VC and non-­‐backed firms before the first round of VC financing, there are significant differences in the first years after the investment event.95 3.3.2 Current trends for VC activity in the EU VC funding can be used to identify successful innovations and R&D commercialization by industry and country. 82
J A Timmons and W D Bygrave, "Venture Capital's Role in Financing Innovation for Economic Growth," Journal of Business Venturing 1, no. 2 (1986). 83
T Hellmann and M Puri, "The Interaction between Product Market and Financing Strategy: The Role of Venture Capital," Review of Financial Studies 13, no. 4 (2000). 84
S Kortum and J Lerner, "Assessing the Contribution of Venture Capital to Innovation," RAND Journal of Economics 31, no. 4 (2000). 85
Bottazzi and Da Rin, "Venture Capital in Europe and the Financing of Innovative Companies." 86
A Popov and P Roosenboom, "Venture Capital and Patented Innovation: Evidence from Europe," ibid.27 (2012)., 87
G Geronikolaou and G Papachristou, "Venture Capital and Innovation in Europe," Modern Economy 3 (2012). 88
see for instance D J Denis, "Entrepreneurial Finance: An Overview of the Issues and Evidence," Journal of Corporate Finance 10, no. 2 (2004); P A Gompers and J Lerner, "The Venture Capital Revolution," Journal of Economic Perspectives 15, no. 2 (2001).. 89
H J Sapienza, "When to Venture Capitalists Add Value?," Journal of Business Venturing 7, no. 1 (1992); S N Kaplan and P Stromberg, "Financial Contracting Theory Meets the Real World: An Empirical Analysis of Venture Capital Contracts," Review of Economic Studies 70, no. 2 (2003); J Lerner, "Venture Capital and the Oversight of Private Firms," Journal of Finance 50, no. 1 (1995)., 90
D H Hsu, "Venture Capitalists and Cooperative Start-­‐up Commercialization," Management Science 52, no. 2 (2006); L Lindsey, "Blurring Firm Boundaries: The Role of Venture Capital in Strategic Alliances," Journal of Finance 63, no. 3 (2008); M G Colombo, L Grilli, and E Piva, "In Search for Complementary Assets: The Determinants of Alliance Formation of High-­‐Tech Start-­‐Ups," Research Policy 35, no. 8 (2006). 91
F Bertoni, M G Colombo, and L Grilli, "Venture Capital Financing and the Growth of High-­‐Tech Start-­‐Ups: Disentangling Treatment from Selection Effects," ibid.40, no. 7 (2011). 92
N Rosenbusch, J Brinckmann, and V Muller, "Does Acquiring Venture Capital Pay Off for the Funded Firms? A Meta-­‐Analysis on the Relationship between Venture Capital Investment and Funded Firm Financial Performance," Journal of Business Venturing 28, no. 3 (2012). 93
Ibid. 94
Faria and Barbosa, "Does Venture Capital Really Foster Innovation?." 95
A Croce, J Marti, and S Murtinu, "The Impact of Venture Capital on the Productivity Growth of European Entrepreneurial Firms: 'Screening' or 'Value Added' Effect?," Journal of Business Venturing 28, no. 4 (2014). 27 Figure 3.6 below presents VC by European country between 2009-­‐2014. In this figure one clearly observes that the UK has been leading across all financing vehicles (VC, Corporate VC, Private equity, Angel, other) followed by Germany, France, Netherlands and Finland. Larger deals (>500 million USD) tend to capture the bulk of invested funds across countries as these reflect more mature and often less risky propositions. Nevertheless as the breakdown of deals96 reveals their distribution is heavily skewed towards smaller deals (less than 5 million USD) while fewer companies secure more than 25 million USD in further financing rounds. This is partly attributed to the low survival rates for angel/seed-­‐funded projects and premature exits that prevent firms from reporting later stages of financing activity. Figure 3.7, also below, presents an analysis of number of VC round by country over 2011-­‐2013. The gross numbers of VC rounds suggest that the US leads both in scale and intensity of activity. However, accounting for population (VC intensity), the leading countries in Europe are Ireland (15.9 rounds per million population) and Denmark (9.40 rounds per million population); Ireland reports almost twice the score of the UK (8.5 rounds per million population) and is much closer to the US (23.9 rounds per million population). Figure 3.6: VC by country ($) 2012-­‐201497 96
Deals are financing agreements across different rounds for venture-­‐backed companies. The 2014 data were updated in July 2014. 97
28 Figure 3.7: Top countries by VC rounds Figure 3.8 below presents an analysis of the VC investments by region. The model of innovation deriving from top universities combined with a pro-­‐investment culture created the most successful place for venture capital investments, the Silicon Valley. In the first seven months of 2014 the cumulative amounts placed in VC rounds in SF Bay Area98 exceeded 14.6 billion USD more than the sum of the next twelve cities VC activity combined. Apart from London there is no other European city featuring in the top-­‐20 global cities of the world. This finding underlines the current situation in Europe compared to the rest of the world. 98
The Bay Area includes the SF metropolitan area. 29 Figure 3.8: Top regions by Investment Moving from the national statistics to specific industries, the key sectors attracting VC funds are core ICT sectors like software, Internet services, mobile app and mobile services firms. The non-­‐ICT sector includes healthcare, green-­‐tech and other applications. It is hard to draw a line between ICT and non-­‐ICT investments as the majority of healthcare and green-­‐tech deals are based on substantial elements of modern electronics and applications. Nevertheless, as long as the key contribution of the service or product is not ICT related we do not label them as ICT. The majority of deals across Europe (38%) are for Internet service firms (2009-­‐2014) followed by healthcare (18%) and mobile (12%).99 Green-­‐tech and healthcare have generally higher deals as the equipment and research in these areas often requires substantial upfront investments. Internet and mobile service sectors are the most dynamic growing with more than 45% every year in cumulative deals since 2009. The UK leads in scale across sectors. Sweden has strong startups in mobile payments, web hosting, agricultural applications and nanotechnologies; Netherlands in analytics, clean technologies and app marketing; the UK in telecoms, mobile, education technologies and finance services; Germany in e-­‐commerce, biotechnology and hospitality services; France in entertainment, clean technologies, brand marketing and biotechnology; Italy in travel and tourism apps, manufacturing innovations and advertising; Finland in mobile apps, games, health and wellness and cloud computing services; Spain in public relations, fashion and design apps.100 This breadth of specialization across Europe is remarkable. However, what happens to these successful firms when they start to grow and scale? In principle there are three options for every VC backed firm: the first is to continue to grow building on the same trajectory of VC funding until it reaches an IPO – provided the company is successful down this path. The second is to exit the market through and acquisition by a competitor or other firm/fund. The last is to leave the market. For our analysis we focus on market exits as the majority of 99
CB Insights data (2014). TechCrunch database 2014. 100
30 successful startups exit the market before reaching an IPO. To test this we compare the investor country of origin for VC backed firms in Europe and the US. Figure 3.9 below presents the analysis of acquisitions by US investors by country. In USA indigenous firms and individuals make almost 80% of acquisitions. In Europe the situations is different, as local firms and individuals do not invest in these firms with the same “passion”. In fact Americans buy many successful European startups (46% in 2014) while this rate is gradually decreasing. Figure 3.9: Percent of total acquisitions by US investors by country Apart from the commercialization gap identified across Europe and the US, we also observe a limited investment appetite or risk aversion for these firms. The reason behind this may be both resource-­‐
driven and cultural. There is a chance that European countries start to gradually exploit local research and development through the commercialization and resale of early stage startups. It takes time to devise and implement successful investment strategies for high-­‐risk portfolios especially in an uncertain macroeconomic environment. From our analysis it is clear that much of the research in Europe remains unexploited and the most innovative firms are further bought by foreign investors. Although Europe has started to catch up with new ideas and risk capital, it still lacks the means to retain its best firms and talent at home. We identify two main reasons for this. First, the fragmented digital market poses substantial legal, regulatory, linguistic and cultural barriers for successful startups to scale. A potential market of 500 million is underexploited by the lack of coordination and regulatory inertia. Second, the global scarcity of skills creates real growth constraints for smaller firms residing in the region. The most talented people will naturally move to the US where firms spend less for red tape and rewards for individuals are higher. We argue that EU Commission initiatives should be complemented with regulatory changes that help bridge those gaps and turn them in favor of EU countries. If this trend is not tackled and reversed, the region will continue to supply US ICT firms with rare and valuable resources – individuals capable of creating high-­‐growth firms and the ideas embodied in the products of startup companies. Amplifying these concerns, we observe that during the first eight months of 2014 European tech startups have attracted more than USD$28 billion by US investors. Given that the growth potential realized in these firms is appropriated outside Europe we conclude that the difficulties to scale at home should be addressed as a first priority. 31 4.0 •
SUMMARY ICT has a measureable footprint in the European economy, substantially driving economic growth and development. The core ICT industries reap the benefits first; spillover effects affect all industries with a time-­‐lag. •
ICT investments have a dual effect: a direct impact from increased capacities (processing information at higher speeds and dealing with greater data volumes) and an indirect impact via induced management and organizational changes. Based on these effects we identify a capital intensive approach (UK) and an ICT re-­‐organization approach (Finland, Sweden, Germany) pertaining to the sectoral composition of these economies (financial services and manufacturing). We identify exemplars of efficient allocation of resources (Finland) and laggards where institutional and cultural barriers prevented the “expected” effects of ICT capital deepening (Italy, Spain) •
Firm investments in research and development (R&D) in absolute terms increase with company size, revenues and experience. The intensity of R&D investments per sales follows an inverse path: young and small ICT companies lead by orders of magnitude. •
ICT intellectual property (IP) creation and specialization patterns are diverse across countries but in terms of scale, Germany remains an undisputed leader. Finland and Sweden are global leaders in digital communications and computer technologies in patents per capita. Germany has a remarkable breadth of patenting activities in the ICT spectrum while France has some competencies in core technological sectors. Italy and Spain score poorly in most categories. •
ICT micro entrepreneurship through venture capital (VC) is dominated by the UK; London is the only European city among the top 20 global agglomerations of VC activities. Other countries gradually adopt this model too (Germany, Finland, Netherlands, and Spain). However, most European VC-­‐backed firms are later acquired by US investors suggesting a limited availability of risk capital for scaling innovative firms in the region. 32 5.0 RECOMMENDATIONS ICT investments continue to drive overall economic development in Europe. It is therefore essential for European economies to realize the full potential of the continuing dynamism of the ICT sector and encourage ICT adoption and innovation by enhancing entry and competition across the Euro-­‐
zone. Domestic and protected sectors that are little affected by foreign competition are much less likely to invest and benefit from state-­‐of-­‐the-­‐art ICT applications. Much of R&D is investment in knowhow and high-­‐level skills. European policies should continue to encourage the R&D energy arising from small and young firms. In particular, it is important to assess whether R&D policies crowd out private investment by large firms or whether they truly encourage innovation by financially constrained firms – typically small and young firms – that otherwise would not have been able to invest. There is wide variation in patterns of and expertise in ICT invention among EU countries. The commercial exploitation of these ICT specializations seems to diverge from the substantial innovation policy efforts within Europe. It appears that EU countries often fail to commercially capitalize on their technological advantages. Thus, although each of the EIT ICT Labs countries has key technology areas where they stand out, companies that commercialize these inventions do not necessarily become global leaders in their fields. It is the commercialization stage where European innovators meet the most challenges. Innovation policies have recently shifted from generic new firm creation (through R&D or startup subsidies) into creating high-­‐impact startups. The realization that dynamic new firms are responsible for much of job creation and associated macroeconomic benefits has led to the attempts to create “entrepreneurship ecosystems” focusing on business acceleration via incubation, advisory, and venture capital (VC) support. While one quarter of all accelerators in the world are located in Europe, the majority of such schemes lack intra-­‐sector coordination across European countries and a clear focus on systemic constraints (tax rates, financing, ease of doing business, etc.). It remains difficult to build and scale innovative technology businesses in Europe. First, the fragmented European digital market poses substantial legal, regulatory, linguistic and cultural barriers for promising startups to scale. Second, the scarcity of skills and in some cases financial capital creates real growth constraints for smaller firms residing in the region. If this trend is not tackled and reversed, the region will continue to supply the US ICT sector with an extremely scarce resource – individuals capable of creating high-­‐growth firms. Tech startups have attracted more than USD$28 billion by US investors in the first 8 months of 2014. The economic value created by these firms is appropriated outside Europe given the difficulties to scale at home. Moreover, engineers and programmers are often better off joining an established ICT firm instead of proceeding with a new venture. This further reinforces the misallocation of talent to less high-­‐impact activities. Therefore, ensuring sufficient VC and IPO markets in European countries is a high-­‐priority policy initiative. The EIT ICT Labs countries are in many ways ahead of the rest of Europe, but much remains to be done to enhance the governance of innovation. Our key takeaway is that EU countries – even the leading ones – need to further their efforts to fund and nurture innovative startups and individuals in Europe. To retain successful startups and individuals in Europe we recommend that policy makers mobilize and maintain a sustainable entrepreneurship ecosystem in Europe. 33 European policy implications EU countries – even the leading ones – need to intensify their efforts to grow and retain successful ICT startups and innovators in Europe. Current national and regional policies aim to promote entrepreneurship to instill a cultural change and encourage productive risk taking. However, when successful firms do emerge, these policies are not sufficiently helping them scale and grow beyond national borders. During the startup growth phase, many successful EU firms and their leaders move – their equity, themselves or both – to the US. Addressing the fundamental causes for this “leak” is the next big challenge for the EU entrepreneurship action plans. For this we recommend a set of policies below. First, maintain and strengthen commercialization of technological invention. It is important to expand and coordinate incubator and accelerator programs in the region. The current focus overlooks the potential for ideas that take longer to mature and materialize. These programs should further aim to link research outputs to innovative entrepreneurial ideas. Direct connection with universities and research centers can improve knowledge exchange thus reinforcing the learning process and broadening their reach. ð EIT ICT Labs can further enhance the adoption of leading-­‐edge ICTs in user industries. For example, governments or EIT ICT Labs can increase funded technology transfer and adoption programs for ICT innovation in financial services, healthcare, cultural industries (games, music, news, books…), government, or networked utilities, such as electricity or telecommunications. Industries heavily dependent on information processing and subject to international competition may be the most likely to make significant progress and generate spillovers for other industries in the process. ð EIT ICT Labs can accelerate the expansion of management education of ICT innovators. Commercialization and entrepreneurship require capabilities that are very distinct from technology development, and individuals trained in technology will not automatically be experts in management and commercialization. “Conversion” programs at leading technology universities where engineering graduates take a one-­‐year program in business management and entrepreneurship might substantially enhance these individuals’ capacity to start and grow innovative companies. We also recommend the development of innovation management programs for young professionals (sometimes called executive education or technology leadership programs). EIT ICT Labs could strengthen its role in shaping and connecting promising young professionals from ICT companies with leadership and innovation training in leading business schools. Second, policy makers need to address systemic constraints across EU countries. These range from corporate and income taxation, access and conditions to financing (including VC), bankruptcy law and other sector-­‐specific bureaucratic processes within and across countries. The economic recession has catalyzed a number of changes in this direction but a lot remains to be done. Realizing these limitations in generic entrepreneurial policies and approaching the startup lifecycle in a holistic manner can help capture much of the lost potential in Europe. ð EIT ICT Labs can facilitate expansion of financial options for innovation by small and young firms. These can, for example, consist of low-­‐interest loans or technology-­‐
development grants (cf. SBIR in the United States), in addition to early-­‐stage and growth-­‐
stage venture capital. For example, EIT ICT Labs could facilitate connecting the knowledge creation programs (education or young professional programs) with specialized financial services (e.g. venture capital firms) through business plan competitions. Similarly, EIT ICT Labs could work with the financial centres of London and Frankfurt in discovering methods to financially retain ICT innovations and innovators in 34 Europe. EIT ICT Labs can also bridge and connect financial and technological capabilities at the European level. Coordination and cooperation with the European Investment Fund is also an important opportunity. Third, support and guide firms to scale across Europe in a digital market of more than 500 million customers. The current situation reflects 28 different markets with cultural, legal and linguistic differences. Coordination among member states can drastically reduce this burden for companies. The fact more than 300 million customers reside in the five largest countries that could be the first step in this direction. ð EIT ICT Labs could play an important role in lowering the expansion hurdles for startups wanting to grow outside of their home country. Providing the local expertise in major European countries to avoid pitfalls, cutting through red tape and provide access to the local entrepreneurship ecosystem could be a major factor in encouraging startups to grow within Europe. Fourth, connect, train, and mentor innovators in Europe – there is much more to gain from joint efforts based on the remarkable research outputs of EU countries. The UK already reaps the benefits from this change with London being the most active startup community in Europe but only sixth in the world; the top spots are taken by three US and two Asian hubs in 2014. ð EIT ICT Labs can significantly contribute to the building and mobilization of networks of experienced innovators and entrepreneurs. One way to facilitate sharing and expansion of commercialization capabilities is by connecting experienced technology entrepreneurs (“serial entrepreneurs”) with newcomers. EIT ICT Labs could facilitate these connections and mentoring between experienced and new tech entrepreneurs. Even if the former are not in financial positions to become angel investors, they might be willing to engage as active board members in young tech companies. In a nutshell what needs to be done is to mobilize and maintain a sustainable entrepreneurship ICT ecosystem in Europe. To do so, all aspects of innovation lifecycle from R&D to startup creation to maturity need to be addressed. At this point the focus is heavily drawn on the creation and commercialization of ideas -­‐ which represents a reasonable first bet for the EU. However we argue that Europe needs to find ways to retain its global pioneers and support their contributions to cultural and economic change. ð The final suggested action for EIT ICT Labs is to connect and coordinate the above programs across European countries. For example, mentoring and training programs could ideally be accessible for technology experts and inventors from all European countries. Engineering and business students and startups as well as entrepreneurs, VC and incumbents across European countries could also be brought together for venture competitions. This would expose all stakeholders along the innovation pipeline to other parts of the European market and also to innovative competition across countries. 35 APPENDIX 1 – Methods We follow and expand the work of O'Mahony and Timmer (2009) in this section. This methodology is based on production possibility frontiers where industry gross output is a function of capital, labor, intermediate inputs and technology. The production function, indexed by time T, is given by: 𝑌! = 𝑓 𝐾! , 𝐿! , 𝑋! , 𝑇 (1) where each industry is indexed by j, Y is output, K is an index of capital flows, L is an index of labor service X is an index of intermediate inputs (purchased or imported) and A (a measure of technological change). Transforming this into a translog functional form we get:101 !
!
!
𝛥𝑙𝑛𝑌!" = 𝑣!"
𝛥𝑙𝑛𝐾!" + 𝑣!"
𝛥𝑙𝑛𝐿!" + 𝑣!"! 𝛥𝑙𝑛𝑋!" + 𝛥𝑙𝑛𝐴!"
(2) where 𝑣 ! denotes the average share of input i in nominal output defined as follows: !
𝑣!"
=
!
!!"
!!"
!
!!"
!!"
; !
𝑣!"
=
!
!!"
!!"
!
!!"
!!"
; 𝑣!"! =
!
!!"
!!"
!
!!"
!!"
(3) and 𝑣 ! + 𝑣 ! + 𝑣 ! = 1. For our analysis we look into ICT and non-­‐ICT capital dividing the capital input growth into two groups of assets: 𝛥𝑙𝑛𝐾!" = 𝑤!"!"# 𝛥𝑙𝑛𝐾!"!"# + 𝑤!"! 𝛥𝑙𝑛𝐾!"! (4) where 𝑤!"!"# is the share of ICT-­‐asset k in total ICT capital costs in industry j and similarly for non ICT assets. From (2) and (4) we get: !
!
𝛥𝑙𝑛𝑌!" = 𝑤!"!"# 𝛥𝑙𝑛𝐾!"!"# + 𝑤!"! 𝛥𝑙𝑛𝐾!"! + 𝑣!"
𝛥𝑙𝑛𝐿!" + 𝑣!"! 𝛥𝑙𝑛𝑋!" + 𝛥𝑙𝑛𝐴!"
(5) The contribution of capital input is the product of its share in total costs and its growth rate. Any remaining output growth is picked up by the multi-­‐factor productivity term A also known as total factor productivity. 101
Under the assumptions of competitive factor markets, full input utilization and constant returns to scale. 36 APPENDIX 2 – ICT patents detail Table A2.1: IPC classes used for ICT patents IPC G: Physics Description
G01P
G01R
G01S
G01V
MEASURING; TESTING G01M
TESTING STATIC OR DYNAMIC BALANCE OF MACHINES OR STRUCTURES; TESTING OF STRUCTURES OR APPARATUS, NOT OTHERWISE PROVIDED FOR MEASURING LINEAR OR ANGULAR SPEED, ACCELERATION, DECELERATION OR SHOCK; INDICATING PRESENCE OR ABSENCE OF MOVEMENT; INDICATING DIRECTION OF MOVEMENT MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES RADIO DIRECTION-­‐FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-­‐
DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES GEOPHYSICS; GRAVITATIONAL MEASUREMENTS; DETECTING MASSES OR OBJECTS; TAGS OPTICAL ELEMENTS, SYSTEMS, OR APPARATUS G03G
DEVICES OR ARRANGEMENTS, THE OPTICAL OPERATION OF WHICH IS MODIFIED BY CHANGING THE OPTICAL PROPERTIES OF THE MEDIUM OF THE DEVICES OR ARRANGEMENTS FOR THE CONTROL OF THE INTENSITY, COLOUR, PHASE, POLARISATION OR DIRECTION OF LIGHT, e.g. SWITCHING, GATING, MODULATING OR DEMODULATING; TECHNIQUES OR PROCEDURES FOR THE OPERATION THEREOF; FREQUENCY-­‐
CHANGING; NON-­‐LINEAR OPTICS; OPTICAL LOGIC ELEMENTS; OPTICAL ANALOGUE/DIGITAL CONVERTERS PHOTOMECHANICAL PRODUCTION OF TEXTURED OR PATTERNED SURFACES, e.g. FOR PRINTING, FOR PROCESSING OF SEMICONDUCTOR DEVICES; MATERIALS THEREFOR; ORIGINALS THEREFOR; APPARATUS SPECIALLY ADAPTED THEREFOR ELECTROGRAPHY; ELECTROPHOTOGRAPHY; MAGNETOGRAPHY G03H
HOLOGRAPHIC PROCESSES OR APPARATUS G04G
ELECTRONIC TIME-­‐PIECES G05B
G05D
CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS SYSTEMS FOR CONTROLLING OR REGULATING NON-­‐ELECTRIC VARIABLES G05F
SYSTEMS FOR REGULATING ELECTRIC OR MAGNETIC VARIABLES G06C
DIGITAL COMPUTERS IN WHICH ALL THE COMPUTATION IS EFFECTED MECHANICALLY PHOTOGRAPHY; CIN
EMATOGRAPHY; AN
ALOGOUS TECHNIQUES USING CONTROLLING;
HOROLOGY WAVES OTHER REGULATING THAN OPTICAL WAVES; ELECTROGR
APHY; HOLOGRAPH
Y G02F
OPTICS G02B
G06D
G06E
G06F
G06G
G06J
G06K
G06M
G06N
DIGITAL FLUID-­‐PRESSURE COMPUTING DEVICES OPTICAL COMPUTING DEVICES ELECTRIC DIGITAL DATA PROCESSING ANALOGUE COMPUTERS HYBRID COMPUTING ARRANGEMENTS RECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS COUNTING MECHANISMS; COUNTING OF OBJECTS NOT OTHERWISE PROVIDED FOR COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS IMAGE DATA PROCESSING OR GENERATION, IN GENERAL G07B
TICKET-­‐ISSUING APPARATUS; TAXIMETERS; ARRANGEMENTS OR APPARATUS FOR COLLECTING FARES, TOLLS OR ENTRANCE FEES AT ONE OR MORE CONTROL POINTS; FRANKING APPARATUS TIME OR ATTENDANCE REGISTERS; REGISTERING OR INDICATING THE WORKING OF MACHINES; GENERATING RANDOM NUMBERS; VOTING OR LOTTERY APPARATUS; ARRANGEMENTS, SYSTEMS, OR APPARATUS FOR CHECKING NOT PROVIDED FOR ELSEWHERE REGISTERING THE RECEIPT OF CASH, VALUABLES, OR TOKENS G08B
G08C
G08G
G09B
G09C
G09D
G09F
G09G
G10F
G10G
MUSICAL EDUCATING; CRYPTOGRAP
INSTRUM
HY; DISPLAY;ADVERTISING SIGNALLING ENTS; AC
; SEALS OUSTICS G07G
CHECKING-­‐
DEVICES G06T
G07C
COMPUTING; CALCULATING; COUNTING G03F
SIGNALLING OR CALLING SYSTEMS; ORDER TELEGRAPHS; ALARM SYSTEMS TRANSMISSION SYSTEMS FOR MEASURED VALUES, CONTROL OR SIMILAR SIGNALS TRAFFIC CONTROL SYSTEMS EDUCATIONAL OR DEMONSTRATION APPLIANCES; APPLIANCES FOR TEACHING, OR COMMUNICATING WITH, THE BLIND, DEAF OR MUTE; MODELS; PLANETARIA; GLOBES; MAPS; DIAGRAMS CIPHERING OR DECIPHERING APPARATUS FOR CRYPTOGRAPHIC OR OTHER PURPOSES INVOLVING THE NEED FOR SECRECY RAILWAY OR LIKE TIME OR FARE TABLES; PERPETUAL CALENDARS DISPLAYING; ADVERTISING; SIGNS; LABELS OR NAME-­‐PLATES; SEALS ARRANGEMENTS OR CIRCUITS FOR CONTROL OF INDICATING DEVICES USING STATIC MEANS TO PRESENT VARIABLE INFORMATION AUTOMATIC MUSICAL INSTRUMENTS AIDS FOR MUSIC; SUPPORTS FOR MUSICAL INSTRUMENTS; OTHER AUXILIARY DEVICES OR ACCESSORIES FOR MUSIC OR MUSICAL INSTRUMENTS 37 G10L
ELECTROPHONIC MUSICAL INSTRUMENTS; INSTRUMENTS IN WHICH THE TONES ARE GENERATED BY ELECTROMECHANICAL MEANS OR ELECTRONIC GENERATORS, OR IN WHICH THE TONES ARE SYNTHESISED FROM A DATA STORE SOUND-­‐PRODUCING DEVICES (sound-­‐producing toys A63H 5/00); METHODS OR DEVICES FOR PROTECTING AGAINST, OR FOR DAMPING, NOISE OR OTHER ACOUSTIC WAVES IN GENERAL; ACOUSTICS NOT OTHERWISE PROVIDED FOR SPEECH ANALYSIS OR SYNTHESIS; SPEECH RECOGNITION; SPEECH OR VOICE PROCESSING; SPEECH OR AUDIO CODING OR DECODING G11B
INFORMATION STORAGE BASED ON RELATIVE MOVEMENT BETWEEN RECORD CARRIER AND TRANSDUCER STATIC STORES G10H
INFO STORAGE G10K
G11C
IPC H: Electricity Description RESISTORS H01F MAGNETS; INDUCTANCES; TRANSFORMERS; SELECTION OF MATERIALSFOR THEIR MAGNETIC PROPERTIES H01G CAPACITORS; CAPACITORS, RECTIFIERS, DETECTORS, SWITCHING DEVICES, LIGHT-­‐SENSITIVE OR TEMPERATURE-­‐SENSITIVE DEVICES OF THE ELECTROLYTIC TYPE H01H H01J H01L H01M BASIC ELECTRIC ELEMENTS H01C ELECTRIC SWITCHES; RELAYS; SELECTORS; EMERGENCY PROTECTIVE DEVICES ELECTRIC DISCHARGE TUBES OR DISCHARGE LAMPS SEMICONDUCTOR DEVICES; ELECTRIC SOLID STATE DEVICES NOT OTHERWISE PROVIDED FOR PROCESSES OR MEANS, e.g. BATTERIES, FOR THE DIRECT CONVERSION OF CHEMICAL ENERGY INTO ELECTRICAL ENERGY H01P WAVEGUIDES; RESONATORS, LINES OR OTHER DEVICES OF THE WAVEGUIDE TYPE H01Q AERIALS H01R ELECTRICALLY-­‐CONDUCTIVE CONNECTIONS; STRUCTURAL ASSOCIATIONS OF A PLURALITY OF MUTUALLY-­‐INSULATED ELECTRICAL CONNECTING ELEMENTS; COUPLING DEVICES; CURRENT COLLECTORS H01S DEVICES USING STIMULATED EMISSION H02B BOARDS, SUBSTATIONS, OR SWITCHING ARRANGEMENTS FOR THE SUPPLY OR DISTRIBUTION OF ELECTRIC POWER H02H H02J H02M H02P GENERATION, CONVERSION, OR DISTRIBUTION OF ELECTRIC POWER H02G H03F H03G H03H H03J BASIC ELECTRONIC CIRCUITRY H03D EMERGENCY PROTECTIVE CIRCUIT ARRANGEMENTS CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY APPARATUS FOR CONVERSION BETWEEN AC AND AC, BETWEEN AC AND DC, OR BETWEEN DC AND DC, AND FOR USE WITH MAINS OR SIMILAR POWER SUPPLY SYSTEMS; CONVERSION OF DC OR AC INPUT POWER INTO SURGE OUTPUT POWER; CONTROL OR REGULATION THEREOF CONTROL OR REGULATION OF ELECTRIC MOTORS, GENERATORS, OR DYNAMO-­‐ELECTRIC CONVERTERS; CONTROLLING TRANSFORMERS OR REACTORS OR CHOKE COILS GENERATION OF OSCILLATIONS, DIRECTLY OR BY FREQUENCY-­‐CHANGING, BY CIRCUITS EMPLOYING ACTIVE ELEMENTS WHICH OPERATE IN A NON-­‐SWITCHING MANNER; GENERATION OF NOISE BY SUCH CIRCUITS H03B H03C INSTALLATION OF ELECTRIC CABLES OR LINES, OR OF COMBINED OPTICAL AND ELECTRIC CABLES OR LINES MODULATION DEMODULATION OR TRANSFERENCE OF MODULATION FROM ONE CARRIER TO ANOTHER AMPLIFIERS CONTROL OF AMPLIFICATION IMPEDANCE NETWORKS, e.g. RESONANT CIRCUITS; RESONATORS TUNING RESONANT CIRCUITS; SELECTING RESONANT CIRCUITS 38 PULSE TECHNIQUE H03K H03L AUTOMATIC CONTROL, STARTING, SYNCHRONISATION, OR STABILISATION OF GENERATORS OF ELECTRONIC OSCILLATIONS OR PULSES H03M CODING, DECODING OR CODE CONVERSION, IN GENERAL H04B TRANSMISSION H04J H04K H04L H04M H04N ELECTRIC COMMUNICATION TECHNIQUE H04H H05K ELECTRIC TECHNIQUES NOT OTHERWISE PROVIDED FOR H05H MULTIPLEX COMMUNICATION SECRET COMMUNICATION; JAMMING OF COMMUNICATION TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION TELEPHONIC COMMUNICATION PICTORIAL COMMUNICATION, e.g. TELEVISION SELECTING H04Q H05C BROADCAST COMMUNICATION ELECTRIC CIRCUITS OR APPARATUS SPECIALLY DESIGNED FOR USE IN EQUIPMENT FOR KILLING, STUNNING, ENCLOSING OR GUIDING LIVING BEINGS PLASMA TECHNIQUE PRINTED CIRCUITS; CASINGS OR CONSTRUCTIONAL DETAILS OF ELECTRIC APPARATUS; MANUFACTURE OF ASSEMBLAGES OF ELECTRICAL COMPONENTS B07C B41J B41L B41M PRINTING; LINING MACHINES; SORTING TYPEWRITERS; STAMPS IPC operations; Transporting B — P erforming POSTAL SORTING; SORTING INDIVIDUAL ARTICLES, OR BULK MATERIAL FIT TO BE SORTED PIECE-­‐MEAL, e.g. BY PICKING TYPEWRITERS; SELECTIVE PRINTING MECHANISMS, i.e. MECHANISMS PRINTING OTHERWISE THAN FROM A FORME;CORRECTION OF TYPOGRAPHICAL ERRORS APPARATUS OR DEVICES FOR MANIFOLDING, DUPLICATING, OR PRINTING FOR OFFICE OR OTHER COMMERCIAL PURPOSES; ADDRESSING MACHINES OR LIKE SERIES-­‐PRINTING MACHINES PRINTING, DUPLICATING, MARKING, OR COPYING PROCESSES; COLOUR PRINTING 39 Table A2.2 Global ICT patent leaders and specialists 2013 Specialist B07C Postal sorting B41J Typewriters; selective printing mechanisms, B41L Apparatus or devices for manifolding, duplicating, or printing for office or other commercial purposes; addressographs or like series-­‐printing machines Netherlands B41M G01R Leader Germany Granted by the USPTO Specialist Netherlands Leader USA Japan Japan Japan Japan USA Japan Spain Japan Printing, duplicating, marking, or copying methods; colour printing Belgium Japan Japan USA Measuring electric variables; measuring magnetic variables Finland USA Italy USA G01S Radio direction-­‐finding; Radio navigation Hungary Germany G02B Optical elements, systems, or apparatus Belgium Japan Japan Japan Japan Japan G02F G03F G03G G05B Devices or arrangements, the optical operation of which is modified by changing the optical properties of the medium of the devices or arrangements for the control of the intensity, colour, phase, polarisation or direction of light, e.g. Switching, gating, modulating or demodulating; techniques or procedures for the operation thereof; frequency-­‐changing; Photomechanical production of textured or patterned surfaces, e.g. For printing, for processing of semiconductor devices; Materials therefor; originals therefor; Apparatus specially adapted therefore Electrography; electrophotography; magnetography Control or regulating systems in general; functional elements of such systems; Monitoring or testing arrangements for such systems or elements Netherlands Japan Japan Japan Japan Germany Germany Japan G06F Electric digital data processing Hungary USA Finland USA G06K Recognition of data; Presentation of data; Record carriers; Handling record carriers Austria USA Spain USA G06T Image data processing or generation, in general Belgium Japan G08B Signalling or calling systems; Order telegraphs; alarm systems Finland G09G Arrangements or circuits for control of indicating devices using static means to present variable information Japan Japan G11B Information storage based on relative movement between record carrier and transducer Japan Japan Japan Japan G11C Static stores Italy USA H01J Electric discharge tubes or discharge lamps Hungary Japan Italy Germany Belgium Japan Belgium Japan Japan Japan Japan Japan Spain Germany Germany Germany Germany Japan H01L H01M H01R Semiconductor devices; Electric solid state devices not otherwise provided for Processes or means, e.g. Batteries, for the direct conversion of chemical energy into electrical energy Electrically-­‐conductive connections; Structural associations of a plurality of mutually-­‐insulated electrical connecting elements; Coupling devices; current collectors H02J Circuit arrangements or systems for supplying or distributing electric power; Systems for storing electric energy H04B Transmission H04J Multiplex communication H04L USA Finland USA Spain Italy USA Transmission of digital information Hungary USA Hungary USA H04M Telephonic communication Finland USA Belgium USA H04N Pictorial communication Japan Japan Japan Japan H05K Printed circuits; Casings or constructional details of electric apparatus; Manufacture of assemblages of electrical components Japan Germany Austria Japan Granted by the EPO USA 40 Table A2.3: Global ICT patent trends 2011 Granted by the EPO IPC B: Performing Operations; Transporting Specialist B07C B07: SEPARATING SOLIDS FROM SOLIDS; SORTING Granted by the USPTO Leader Specialist Leader Netherlands Germany Belgium USA Japan Japan Netherlands Japan Japan Japan USA USA B41M Japan Japan Belgium Japan G01M Netherlands USA Netherlands USA G01S Netherlands Germany Finland USA G01V UK USA UK USA Belgium Japan Belgium Japan Hungary Japan Japan Japan Japan Japan Netherlands Japan Hungary Germany Finland USA Finland USA France USA France USA Netherlands Japan Netherlands Japan B41J B41L G01R G02B G02F B41: PRINTING; LINING MACHINES; TYPEWRITERS; STAMPS MEASURING; TESTING OPTICS G03G PHOTOGRAPHY; CINEMATOGRAPHY; ELECTROGRAPHY; HOLOGRAPHY G05B CONTROLLING; REGULATING G06F G06K COMPUTING; CALCULATING; COUNTING G06T G08B SIGNALLING G09G EDUCATING; CRYPTOGRAPHY; DISPLAY; ADVERTISING; SEALS Japan Japan Italy Germany Italy Germany Belgium Japan Belgium Japan Japan Japan Japan Japan Germany Germany Germany Germany Germany Japan Germany Japan H02M H04B Spain USA Spain USA Hungary USA Hungary USA Belgium USA Belgium USA Japan Japan Japan Japan Austria Japan Austria Japan H01H H01L H01M BASIC ELECTRIC ELEMENTS H01R H02J GENERATION, CONVERSION, OR DISTRIBUTION OF ELECTRIC POWER H04L H04M ELECTRIC COMMUNICATION TECHNIQUE H04N H05K ELECTRIC TECHNIQUES NOT OTHERWISE PROVIDED FOR 41 APPENDIX 3 – VC by industry sector in Europe Table A3.1: VC by industry by sector in Europe (2009–2014) [Source: CB Insights] Finland Netherlands France Germany UK Europe Internet Mobile Software Healthcare Green tech Other % deals 37.94 12.32 4.05 17.45 5.23 23.01 Avg deals size ($M) 5.65 10.07 9.13 10.60 18.05 41.70 Median deal size ($M) 1.50 1.50 2.00 4.36 4.50 3.60 % deal growth (yoy) 45.56 49.70 19.05 12.18 4.14 22.57 % deals 36.94 10.64 3.41 15.09 6.42 27.51 Avg deals size ($M) 6.06 12.40 5.82 7.30 9.59 22.49 Median deal size ($M) 1.65 1.61 2.20 2.84 4.20 3.00 % deal growth (yoy) 42.01 38.39 26.19 17.70 9.34 26.71 % deals 40.04 13.72 4.42 23.45 3.7 14.60 Avg deals size ($M) 10.50 5.07 3.91 12.34 8.73 42.19 Median deal size ($M) 3.60 2.00 1.65 5.22 8.00 5.23 % deal growth (yoy) 27.54 71.88 31.95 -­‐1.14 -­‐9.71 14.87 % deals 43.94 10.61 6.23 16.16 4.21 18.86 Avg deals size ($M) 5.19 4.48 4.58 10.55 13.07 20.31 Median deal size ($M) 2.20 2.60 2.76 5.81 3.44 4.10 % deal growth (yoy) 20.45 31.95 -­‐14.97 3.30 -­‐3.58 8.06 % deals 30.85 10.45 2.99 30.85 6.47 18.41 Avg deals size ($M) 4.38 3.43 107.37 10.53 12.67 20.94 Median deal size ($M) 1.00 1.20 3.95 6.40 5.94 5.90 % deal growth (yoy) 52.81 8.45 -­‐12.94 0.00 -­‐7.79 8.45 % deals 43.48 30.43 0.00 9.57 1.74 14.78 Avg deals size ($M) 2.42 4.99 0.00 4.38 10.70 7.64 Median deal size ($M) 1.25 1.30 0.00 2.87 10.70 3.00 % deal growth (yoy) 52.81 7.88 N/A N/A N/A 24.57 42 APPENDIX 4 – Databases used in this report EU KLEMS (www.euklems.net) The 2012 EU KLEMS release follows up from the previous release in 2009, which showed detailed growth accounts up to 2007. This new release is similar in concepts and methodologies to calculate the various growth and productivity variables as its predecessors, but it also has a number of new features. It provides updates and data for additional years and revisions of longer time-­‐series in case national statistical institutes (NSIs) provided these. The data on output, value added and employment in EU KLEMS is now fully consistent with the series in the OECD Structural Analysis Database (STAN) at the corresponding industry levels. For labor composition use has been made of the micro-­‐data underlying the European Labor Force Survey (LFS) for recent years. New investment data has been provided by the EU KLEMS consortium partners. Most importantly, a new industrial classification is used based on the new international ISIC Revision 4 industry classification, which is consistent with the European NACE 2 industry classification. The National Accounts (NA) data in the new classification is typically provided for shorter time series than were previously available in the ISIC Rev. 3 (NACE 1) classification. We back-­‐cast time series of output and labor data using growth rates from the earlier data in the ISIC Rev. 3 classification. These imputations are denoted in grey in the new release. We used the EU KLEMS data for our national and industry level analysis of ICT impact on capital deepening and productivity. PatStat – EPO Worldwide Patent Statistical Database (data.epo.org) PATSTAT, also known as the EPO Worldwide Patent Statistical Database, is a snapshot of the EPO master documentation database (DOCDB) with worldwide coverage. It contains more than 20 tables with bibliographic data, citations and family links of about 70 million applications of more than 80 countries. We used the entire database to map innovation spillovers of ICT patents. Orbis/Amadeus (amadeus.bvdinfo.com) Amadeus contains comprehensive information on around 21 million companies across Europe. It contains company information for both Western and Eastern Europe, with a focus on private company information, company financials in a standard format allowing comparisons of companies across borders, financial strength indicators, directors, images of report and accounts for listed companies, stock prices for listed companies, detailed corporate structures, market research, business and company-­‐related news, M&A deals and rumours and maps. We used the Orbis/Amadeus data to assess the level of R&D investments in EU firms for ICT and non-­‐ICT sectors. TechCrunch/ CrunchBase (crunchbase.com) CrunchBase is the world’s most comprehensive dataset of startup activity and it’s freely accessible. Founded in 2007 by Mike Arrington, CrunchBase began as a simple crowd sourced database to track startups covered on TechCrunch. Today it contains about 650k profiles of people and companies that are maintained by tens of thousands of contributors. We used CrunchBase data for the VC analysis of our report. 43 CB Insights (www.cbinsights.com) CB Insights tracks the world's most promising private companies, their investors, their acquirers and the industries they compete in. We used part of CB insights in comparison with CrunchBase data for the EU startup activity. OECD Stat (stats.oecd.org) OECD Stat is the statistical online platform of the OECD where users can search and access OECD’s statistical databases. In our analysis we used the USPTO and EPO patent data by country for several ICT related patent classification. Seed DB (www.seed-­‐db.com) Seed-­‐DB contains a comprehensive list of all known accelerators as well as all of the companies that had gone through those programs. We used Seed-­‐DB in our incubator/accelerator section. 44