CONCEPTUALISING &

MEASURING THE ‘ERIS’

Dimitrios Pontikakis 2,1 Luisa Henriques 3,1 Laura de Dominicis 1

1 European Commission, Joint Research Centre, Institute for Prospective and Technological Studies (IPTS)

2 Newcastle Business School, University of Northumbria3 Portuguese Science and Technology Foundation

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Overview

1. Introduction

2. Definition and components of ERIS

3. Structural Change in the ERIS

4. Conclusions

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ERISThe emerging ERIS can be understood as a

system of research and innovation relations

between actors located inside the borders of

the EU-27 at multiple levels –European,

national and regional – to produce, diffuse and

explore new knowledge for new products,

industrial processes and services for the

benefit European citizens.

ERIS ≠ ERA

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Questions: Following decades of cooperation and integration in

the European research activity, infrastructures, and

policies, is there something like a European

Research and Innovation System (ERIS) in

place?

If so then

What is the structural configuration of ERIS and

what are the (policy) implications of such structure?

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1. Exploratory analysis of the emergence of

ERIS

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What do we know already?

1. European collaborative links are growing faster (Mattson et.al, 2008) and diversified over time (Frenken, 2002, Okubo and Zitt, 2004).

2. There is an increasing European ‘systemness’ (Frenken and Leydersdorff, 2004, Hoekman, 2010; Paier and Scherngell, 2011).

3. European system is emerging as a ‘system of systems’ (Gergersen and Johnson, 1996) similar to the implicit structure described by Caracostas and Soete (1997) post-national system.

4. With an emergent multi-level governance framework for R&I policies (Edler and Kuhlmann, 2005).

5. And European shared values and final aims, but no institutional or geographical delineation (Borrás, 2004).

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European policies trajectories

• 1950s-1970s integration programming and performance in specific areas (JRC, IGO)

• 1970s-2000 coordination of performance (FP, SF)

• Since 2000 coordination of programming in public funding

• Intermingled dynamics

o IntegrationoCoordination

Is ERIS in the making?

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Integrity Distinctiveness

Source: Erawatch

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Quantitative approach to the question of

ERIS• Objective: To measure European integration (/distinctiveness) in S&T• Method:Calculate ratios of intra- over extra-EU co-publications, co

patents, spatial autocorrelation of patent counts between regions in the opposite sides of national borders (“knowledge spillovers”)

• Findings: Evidence of substantial integration in co-patenting (x2

more than non-EU), and co-publication (x4 more than non-EU). However, national borders still matter.

Stability over time.

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2. Structural change in the ERIS

What does measurement tell us?

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Drivers of structural change

• ObjectiveIdentify key factors (/groups of) that drive structural change• Method/dataPanel regression (EU27, 3 time periods over 1991-2006) of

overall shift-share across EPO patent sectors (Y) against GERD, proxies of technological structure (diversity/concentration) and a composite indicator of international Openness (Dreher, 2006)

• FindingsMagnitude of resources impacts negatively. Over time

national systems have become less responsive. Only Openness exerts a positive and quantitatively distinct effect.

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Impact of structural variables on capacities• ObjectiveAssess relationship between structural configuration (e.g.

Concentration/diversity/related variety) and policy approaches (strengthening the strengths/diversifying) on national innovative capacity

• MethodKnowledge production function, panel regression EU 1991-

2006. EPO patents (Y) regressed on various alternative proxies of structure plus control vars.

• FindingsContext matters a lot: Even when individual structural

variables were found to have an effect, the magnitude of this effect as well as its sign (positive/negative) change depending on the group of countries considered.

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Conclusions - 11. Evidence of ERIS in the making – with an

institutional framework closely resembling that of a NIS, with interlinked communities, shared values and purpose

2. Europeanisation processes progress differently in programming and performance. In performance is relatively stagnant close to the limits imposed by cultural-linguistic fault-lines. Programming is advancing faster.

3. National authorities retain an important role namely in creating capabilities and steering national resources.

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Conclusions - 21. Existence of important differences with respect

to structural change between emerging and mature R&I systems.

2. International openness is the single most important driver of structural change – further internationalisation (incl. Europeanisation) should act positively.

3. Our findings from the impact of structural configurations on innovative performance emphasise context-specificity. Familiar caveats against one-size-fits all policies seem particularly relevant to the case of structural change.

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Thank youDimitrios Pontikakis

dimitrios.pontikakis@northumbria.ac.uk

Luisa HenriquesLuisa.henriques@fct.pt

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  Related variety

Unrelated variety

Herfindahl concentration

Overall diversity

Shannon diversity

Duplication wrt to EU27 average

Shift ratio

Concentration in 'high expectation' patenting (ICT, Biotech, Nanotech)

ICT as proportion of manufacturing output

Biotech as proportion of manufacturing output

Belgium -0.4 0.47 -0.43 0.04 0.59 0.47 0.18 0.09 -0.83 -0.04Denmark 0.09 0.13 -0.48 0.12 0.67 0.32 0.24 0.42 0.19 1.53Finland 0.39 0.15 0.27 0.31 -0.59 0.52 -0.21 1.22 0.3 -1Ireland 0.31 0.42 -0.27 0.41 0.29 0.66 0.24 0.58 1.96 1.91United Kingdom 0.33 0.29 -0.4 0.36 0.57 0.91 -1.57 0.67 1.11 0.45Netherlands 0.48 0.21 -0.15 0.39 0.12 0.77 -0.34 1.04 0.03 -0.08Austria 0.5 0.46 -0.47 0.54 0.73 0.74 0.31 -0.44 -0.05 -0.5Sweden 0.56 0.54 -0.32 0.62 0.41 0.95 0.07 0.32 0.41 0.91Germany 0.45 0.37 -0.45 0.46 0.65 1.03 -2.14 -0.22 -0.19 0.02France 0.48 0.39 -0.46 0.49 0.72 1.03 -0.49 0.18 -0.03 0.96Italy 0.42 0.36 -0.4 0.45 0.59 0.52 0.16 -0.66 -0.87 -0.14Spain 0.35 0.38 -0.5 0.42 0.82 0.59 0.36 -0.52 -0.8 -0.6Portugal 0.23 0.15 -0.31 0.22 0.4 -0.41 0.24 -0.61 -0.19 -1.08Greece 0.35 0.32 -0.37 0.38 0.49 0.47 0.22 -0.26 -0.76 -1.18Luxembourg 0.14 -0.09 -0.14 0.03 0.03 -0.77 0.22 -0.98 1.28Estonia -0.64 -0.17 0.53 -0.46 -1.4 -0.84 0.2 2.2 0.53Latvia -1.33 -1.29 1.75 -1.49 -1.81 -2.03 0.19 -0.92Lithuania -0.59 -0.98 1.56 -0.89 -1.52 -1.38 0.19 0.71Slovenia 0.57 0.26 -0.36 0.47 0.4 -0.41 0.22 -0.31 -1 1.01Czech Republic 0.07 -0.21 -0.42 -0.08 0.6 0.06 0.25 -0.53 -0.51 -0.93Hungary -0.4 -0.58 -0.39 -0.55 0.49 0 0.24 -0.14 0.5 -0.17Poland -0.18 -0.17 -0.36 -0.2 0.45 -0.04 0.25 -0.23 -0.84 -0.93Bulgaria 0.07 0.15 0.04 0.12 -0.4 -0.08 0.2 -0.05Romania -0.18 -0.14 0.02 -0.19 -0.51 -0.04 0.2 -0.21Slovakia -0.5 -0.77 0.1 -0.72 -0.44 -0.46 0.21 -0.09 -0.97 -0.96Cyprus -1.38 -0.32 0.62 -0.98 -1.43 -0.82 0.19 -0.71Malta -0.17 -0.32 1.83 -0.28 -2.01 -1.82 0.18 -0.55

Indicators of technological structure (country average scores over 1991-2006 period expressed in standard deviations from cross-country variable mean)

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Direction of technological change vs. policy making

Indicator name Definition Relationship in the system

CA1

Structural correlation between a country's NABS92 distributions of GBAORD with GERD of the year before.

Government SystemPropensity of government R&D funding to direct resources to areas of existing capabilities.

CA2

Structural correlation between a country's NACE distributions of BERD funded by government with BERD of the year before.

Government Private sectorPropensity of government support for private R&D to direct resources to areas of existing capabilities.

CA3

Structural correlation between a country's NACE distributions of BERD with EPO Patents of the year before.

Private sector Technology Propensity of private technology funding in allocating resources to areas of past success.

CA4

Structural correlation between a country's Fields of Science distributions of GERD with Scientific publications of the year before.

System SciencePropensity of public funding for science and markets in allocating resources to areas of past success.

  CA1 CA2 CA3 CA4Belgium 0.82Denmark 0.13 0.81Finland -1.38 0.77Ireland -0.01 1.02 0United Kingdom -1.94Netherlands -0.98 0.65Austria -1.09Sweden 0.86 0.44Germany 0.21 0.18France 1.07Italy -0.09Spain -0.74 0.25 0.56 -0.31Portugal 0.38 -0.14 -0.21 0.22Greece -0.6Luxembourg 1Estonia 0.68 0.88 -0.03 -2.35Latvia 0.88 -0.55 0.11Lithuania 1.11 -0.85 -0.96Slovenia -1.17 -0.58 0.53 1.05Czech Republic 0.02 0.19 -1.83 0.46Hungary 0.19 1.01 -0.82Poland 0.39 0.08 0.72Bulgaria -0.9 0.06 0.13Romania 0.6 -1.31 -0.28 1.27Slovakia 0.31 0.97 0.72 0.33Cyprus -0.21 -0.21 0.43Malta -2.49 -0.08 -1.94 -0.8

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Measuring ERIS : a few optionsSYSTEM PROPERTY CRITERION INDICATOR

INTEGRITY (internal)

COHERENCE(Eqduist, 2001)

-Number of co-publications, co-patents (Number of joint-research projects (FP, COST, EUREKA, TFSD, etc.), including network metrics)

SIMILARITY -Spatial autocorrelation (of resources, capabilities)-Structural correlation (of resources, capabilities)

BALANCE & VARIETY(Stirling, 2007)

-Gini index (of resources, capabilities)

DISTINCTIVENESS (external)

DISTANCE Indicators of functional, technological, cognitive

DISSIMILARITY -Variance of S&T specialisation (e.g. EU vs global)-Structural correlation matrices (of resources, capabilities)

ORIENTATION (inward/outward, Edquist, 2001)

Ratio of inward vs outward: -co-publications (ISI WoK, RKF) -co-patents (OECD Triadic) -joint R&D ventures (TFSD)

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European boundary!European plateau?

199519961997199819992000200120022003200420050

0.5

1

1.5

2

2.5

Intra- over Extra-EU co-publications

Intra- over Extra-EU co-patents

2000 2001 2002 2003 2004 2005 20060.00

0.50

1.00

1.50

2.00

2.50

3.00

3.50

4.00

4.50

EU27 Third Countries

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Knowledge spillovers in border regions

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Impact of structural variables on

capacities

Knowledge outputs

(EPO PATENTS)

Sectoral

Structure

(STRUCTURE)

Existing knowledge

(PSTOCK)

R&D expenditures

(GERD)

Indicator                              Country groups

EU27 EU15 Innovation Leaders & Followers

New Member States

CA1 .. 0.067* .. ..CA2 .. .. .. ..CA3 -0.048** .. .. -0.076**CA4 .. 0.175* .. ..Related variety .. -0.04* .. ..Unrelated variety .. 0.05* .. -0.46*Herfindahl concentration 0.118*** .. 0.079** 0.242***Overall diversity .. .. .. ..Shannon diversity .. .. .. ..Duplication wrt to EU27 average -0.075** .. .. -0.113**Shift ratio .. 0.057** 0.064* ..Concentration in 'high expectation' patenting (ICT, Biotech, Nanotech)

.. .. .. ..

ICT as proportion of manufacturing output

-0.047***

-0.055*** -0.068*** ..

Biotech as proportion of manufacturing output

.. -0.025 -0.036** ..

*, ** and *** denote statistical significance at the 90, 95 and 99% levels respectively.

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Drivers of structural change

• National structural change (measured as the average across sectors of the weight of the country-shift component over total change in patents)

Depends on:• Scale of resources devoted to R&D (proxied by GERD)• The existing structure of the system, which captures its

proximity to emerging or dominant techno-economic paradigms (STRUCTURE, which in this case is a vector of our several alternative proxies of structure)

• International openness (OPENNESS a proxy for which captures the availability of channels for international knowledge transfer and influence on national direction by changes in the global technology frontier).

 STRUCTURAL CHANGE i,t = α + β1ln(GERD i,t)+ β2(STRUCTURE i,t)+ β3(OPENNESS i,t)+u i,t

STRUCTURAL CHANGE i,t =

=146.878*** - 0.23*** ln(GERD i,t) + 0.023*(OPENNESS i,t) – 0.073*(YEAR) + u i,t