Issuu

ADVIES NR 10

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INNOVATIEVE BENCHMARKLANDEN EN -REGIOâ€™S VOOR VLAANDEREN MAART 2020 ////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////

www.vario.be

De Vlaamse Adviesraad voor Innoveren en Ondernemen (VARIO) adviseert de Vlaamse Regering en het Vlaams Parlement over het wetenschaps-, technologie-, innovatie-, industrie-, en ondernemerschapsbeleid. De raad doet dit zowel op eigen initiatief als op vraag. VARIO werd bij besluit opgericht door de Vlaamse Regering op 14 oktober 2016. VARIO werkt onafhankelijk van de Vlaamse Regering en de partijen in het werkveld. De voorzitter en leden van VARIO zetelen in eigen naam: Lieven Danneels (voorzitter)

Koen Vanhalst

Dirk Van Dyck (plaatsvervangend voorzitter)

Vanessa Vankerckhoven

Katrin Geyskens

Marc Van Sande

Wim Haegeman

Reinhilde Veugelers

Johan Martens Het secretariaat is gevestigd in Brussel: Koolstraat 35 1000 Brussel +32 (0)2 553 24 40 vario@vlaanderen.be https://www.vario.be

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INNOVATIEVE BENCHMARKLANDEN EN -REGIO’S VOOR VLAANDEREN Maart 2020

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COLOFON Ontwerp: Vlaamse Overheid/VARIO Maart 2020 Alle publicaties zijn gratis te downloaden via www.vario.be of via https://www.vlaanderen.be/nl/publicaties Coverfoto © www.shutterstock.com

AUTEURSRECHT Alle auteursrechten voorbehouden. Mits de bronvermelding correct is, mogen deze uitgave of onderdelen van deze uitgave worden verveelvoudigd, opgeslagen of openbaar gemaakt zonder voorafgaande schriftelijke toestemming van VARIO. Een correcte bronvermelding bevat in elk geval een duidelijke vermelding van organisatienaam en naam en jaartal van de uitgave.

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INHOUD Managementsamenvatting .............................................................................................................................................................. 6 Executive summary: Innovative benchmark countries and regions for Flanders ...................................... 8 Advies .................................................................................................................................................................................................... 10 1. 2.

Situering Wat verstaat VARIO onder benchmarklanden of –regio’s?

10 10

2.1. 3.

Selectiecriteria Relevante benchmarklanden en -regio’s

10 11

3.1. 3.2.

Gemeenschappelijke kenmerken van benchmarklanden of –regio’s Meest relevante benchmarklanden of –regio’s

11 13

3.3. 4.

Beperkingen van een benchmarkbenadering: het belang van context Referenties

16 17

Appendix I Appendix II Appendix III

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MANAGEMENTSAMENVATTING In het kader van de ambitie van de Vlaamse Regering om de top van kennisen innovatieregio’s te bereiken, vroegen minister-president Jan Jambon en minister van Economie en Innovatie Hilde Crevits relevante Europese benchmarklanden en -regio’s te selecteren (Eerste Fase van de adviesvraag). VARIO selecteerde VIJF INNOVATIEVE BENCHMARKLANDEN: •

Zwitserland, Zweden, Denemarken, Finland en Nederland

Bijkomend werden ZEVENTIEN INNOVATIEVE BENCHMARKREGIO’S geselecteerd: • • • • • •

Zeven uit Zwitserland: Zürich, Région Lémanique, Espace Mittelland, Nordwest-schweiz, Ostschweiz, Zentralschweiz en Ticino Twee uit Zweden: Stockholm en Sydsverige Een uit Denemarken: Hovedstaden Een uit Finland: Helsinki-Uusimaa Twee uit Nederland: Utrecht en Noord-Brabant Vier uit Duitsland: Oberbayern, Karlsruhe, Tübingen en Stuttgart

De geselecteerde landen en regio’s (Figuur 1A) behoren in grote lijnen tot de grote stedelijke agglomeratie de Blauwe Banaan enerzijds, en tot Scandinavië anderzijds. Alhoewel ook Vlaanderen tot de Blauwe Banaan behoort, kunnen we Vlaanderen op dit moment nog niet tot de Europese topregio’s rekenen. De topregio’s Sydsverige (Malmö) en Hovedstaden (Kopenhagen) vormen samen de Zweeds-Deense grensoverschrijdende topregio, met de bekende Sontbrug als fysieke verbinding. VARIO benadrukt dat een benchmarkbenadering altijd beperkingen inhoudt. Er zullen altijd fundamentele (en onveranderbare) verschillen bestaan tussen Vlaanderen en zijn benchmarklanden of regio’s (vb. in economische structuur, infrastructuur, historische beslissingen en investeringen). De context van een land of regio is belangrijk: een goede praktijk in de ene regio kan niet zondermeer worden getransfereerd naar een andere regio. VARIO merkt daarnaast op dat Vlaanderen niet alleen kan leren van succesverhalen, maar tegelijkertijd ook kan leren van landen of regio’s zoals bijvoorbeeld Oostenrijk die in hun strategie gefaald hebben om de top te bereiken. In een Tweede Fase van de adviesvraag zal VARIO tegen de zomer van 2020 concrete aanbevelingen voor een roadmap voor het Vlaams Gewest formuleren, om tegen 2030 aan te sluiten bij de selecte groep van topregio’s. Deze aanbevelingen zullen steunen op een uitgebreide analyse van de rankings (innovatie en competitiviteit), literatuuronderzoek en kwalitatief onderzoek op basis van interviews.

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FIGUUR 1A: Benchmarklanden en -regio’s voor Vlaanderen

Bron: Mapchart.net; Eigen bewerking

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EXECUTIVE SUMMARY: INNOVATIVE BENCHMARK COUNTRIES AND REGIONS FOR FLANDERS As part of the ambition of the Flemish Government to reach the top of knowledge and innovation driven regions, Minister-President Jan Jambon and Minister of Economy and Innovation Hilde Crevits asked to select relevant European benchmark countries and regions (First Phase of the request for advice). VARIO1 selects FIVE INNOVATIVE BENCHMARK COUNTRIES: •

Switzerland, Sweden, Denmark, Finland and The Netherlands.

Additionally, SEVENTEEN INNOVATIVE BENCHMARK REGIONS are selected: • • • • • •

Seven from Switzerland: Zürich, Région Lémanique, Espace Mittelland, Nordwest-schweiz, Ostschweiz, Zentralschweiz and Ticino Two from Sweden: Stockholm and Sydsverige One from Denmark: Hovedstaden One from Finland: Helsinki-Uusimaa Two from the Netherlands: Utrecht and Noord-Brabant Four from Germany: Oberbayern, Karlsruhe, Tübingen and Stuttgart

The selected countries and regions (Figure 1B) largely belong to the large corridor of urbanization the Blue Banana on the one hand, and the Scandinavian countries on the other. Although Flanders belongs to the Blue Banana, we cannot yet count the Flemish Region among the top European regions. The top regions Sydsverige (Malmö) and Hovedstaden (Copenhagen) together, form the Swedish-Danish top cross border innovative region, with the famous Öresund Bridge as its physical link. VARIO emphasizes that a benchmark approach always has its limitations. There will always be fundamental (and immutable) differences between Flanders and its benchmark countries of regions (e.g. in economic structure, infrastructure, historical decisions and investments…). The context of a country or region is always important: a good practice in one region cannot simply be transferred to another. VARIO also notes that Flanders can not only learn from success stories but also from countries or regions such as Austria that have failed in their strategy to reach the top. In a Second Phase of the request for advice, VARIO will formulate concrete recommendations for a roadmap for the Flemish Region by the summer of 2020, in order to join the select group of top regions by 2030. These recommendations will be based on an extensive analysis of the rankings (innovation and competitiveness), literature research and qualitative research based on interviews.

Acronym for The Flemish Advisory Council for Innovation and Enterprise: www.vario.be/en

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FIGURE 1B: Benchmark Countries and Regions for the Flemish Region

Source: Mapchart.net; Own editing

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ADVIES 1. SITUERING In het kader van de ambitie van de Vlaamse Regering om Vlaanderen een top-vijf positie te laten verwerven tussen de meest innovatieve regio’s en landen in Europa, willen minister-president Jan Jambon en minister van Economie en Innovatie Hilde Crevits VARIO actief inschakelen in twee fasen: 1.

In een eerste fase voorstellen te doen voor (1) relevante benchmarklanden en -regio’s, en (2) transparante strategische beleidsindicatoren die periodiek beschikbaar zijn, ook op het niveau van Vlaanderen;

2. In een tweede fase werk te maken van concrete aanbevelingen en adviezen die aansluiten op de eerste fase t.a.v. (1) gerichte optimalisering van het Vlaamse wetenschaps- en innovatiebeleid en onderwijsbeleid om de top-5 ambitie te realiseren; (2) adviezen voor de andere actoren (bedrijven, speerpuntclusters, kennisinstellingen…) om zich hierin te engageren; (3) aanbevelingen t.a.v. een internationaliseringsstrategie en profilering van Vlaanderen als innovatieve topregio. Voorliggend advies beperkt zich tot de 1ste fase van de adviesvraag t.a.v. relevante benchmarkregio’s en/of -landen.

2. WAT VERSTAAT VARIO ONDER BENCHMARKLANDEN OF –REGIO’S? Benchmarklanden en -regio’s zijn Europese referentie- of ‘best practice’-landen en -regio’s die vooroplopen in socio-economische ontwikkeling (economische toplanden of topregio’s, ‘Innovation Powerhouses’…) en waarvan Vlaanderen zoveel mogelijk kan leren, met als ambitie de top van Europa te bereiken van kennisen innovatieregio’s. Voor het bepalen van relevante benchmarkregio’s en -landen baseerde VARIO zich zowel op innovatieals op competitiviteitsindicatoren (Regionaal Innovatiescorebord (RIS), Regionale Competitiviteitsindex (RCI), Europees Innovatie Scoreboard (EIS), WEF Competitiviteitsrapport (GCI), Global Innovation Index (GII)…). Een hoge score op innovatie hangt immers in grote mate samen met sterke prestaties op het gebied van competitiviteit2 of concurrentievermogen, een hoge score op competitiviteit gaat op zijn beurt in sterke mate samen met een hoog Bruto Nationaal Product (BNP) (maar is er niet gelijk aan, zie vb. RCI2019).

2.1.

Selectiecriteria

VARIO maakte maximaal gebruik van volgende selectiecriteria, met het oog op het selecteren van de meest relevante benchmarklanden en -regio’s: 1.

Consistent hoge scores op de meeste indicatoren van zowel innovatie als competitiviteit:

WEF definieert Competitiviteit als volgt: “the set of institutions, policies and factors that determine the level of productivity of a country." Other definitions exist, but all generally include the word “productivity” zie https://www.weforum.org/agenda/2019/10/the-worlds-most-competitive-economies-global-report/ 2

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•

Innovatie: o Europees Innovatie Scorebord (EIS2019): enkel de Innovatieleiders; o Regionaal Innovatie Scorebord (RIS2019): enkel Innovatie Leiders+ en Innovatie Leiders (zonder de Innovation Leaders-) Competitiviteit: o Regionale CompetitiviteitsIndex (RCI2019): Top25 o Globale CompetitiviteitsIndex (WEF) (GCI2019): Top20

2. Consistentie van de scores over de tijd (periode 2011-2019); 3. Agglomeratievoordelen: grootstedelijke regio’s en (hoofd-)steden (capital/metropolitan regions) spelen een belangrijke rol in innovatie en economische competitiviteit (zie vb. EU-RCI, 2019) omwille van agglomeratievoordelen3. Bedrijven, kennisinstellingen, talent… clusteren in elkaars nabijheid, wat leidt tot een aantal baten zoals gemeenschappelijke infrastructuur, toegang tot talent en skills. We nemen bevolkingsdichtheid (aantal inwoners/km²) – samen met de grootte van de regio (NUTS-classificatie) - mee in de analyse (Appendix I, zie ook Appendix II en III: ‘Structural differences’), alhoewel zeker geen perfecte indicator voor agglomeratievoordelen (vb. Ajmone Marsan & Maguire, 2011). Om de vergelijking met Vlaanderen te maken sluiten we de ‘city-success’ regio’s uit, met name die regio’s waar het succes hoofdzakelijk steunt op één bepaalde stad, eerder dan het een succes is voor een hele regio. Dan denken we aan Londen en Berlijn. 4. Vergelijkbare economische structuur (zie profielen van geselecteerde benchmarklanden en -regio’s in Appendix II en III); 5. Regio’s hebben (verregaande) beleidscompetenties m.b.t. innovatie.

3. RELEVANTE BENCHMARKLANDEN EN -REGIO’S In dit hoofdstuk gaat VARIO eerst in op (3.1.) de gemeenschappelijke kenmerken van benchmarklanden of -regio’s, vervolgens (3.2.) op de selectie van een aantal benchmarklanden en -regio’s en ten slotte (3.3.) op de beperkingen van een benchmarkbenadering en de rol van context.

3.1.

Gemeenschappelijke kenmerken van benchmarklanden of –regio’s

Op basis van de analyses van VARIO (Naar de top van kennisen innovatieregio’s, in voorbereiding) blijken topregio’s en toplanden volgende algemene kenmerken gemeenschappelijk te hebben: 1.

Topregio’s scoren consistent hoog op de meeste4 indicatoren van innovatie en competitiviteit. Om een topregio te worden is een globale, brede transformatie nodig met aandacht voor alle ingrediënten van een kennisen innovatiegedreven economie. Dit vergt een uitgesproken kwaliteitsstreven in het hele maatschappelijk weefsel: in het bedrijfsleven, het onderwijs, de

https://nl.wikipedia.org/wiki/Agglomeratie-effect Er bestaat hier zeker een aantal uitzonderingen. We verwijzen hier o.a. naar Nederland dat over het algemeen zeer goed scoort op innovatie- en competitiviteitsindicatoren maar bijvoorbeeld op het aandeel afgestudeerden in de STEM-richtingen zeer laag scoort als rode lantaarn in Europa. 3 4

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overheidsdiensten… Het is een EN-EN-verhaal met een cultuur van innovatie, ambitieus ondernemen en internationalisering als de hoofdingrediënten5. O&O-investeringen, levenslang leren… zijn slechts een deel van een complexe puzzel; ook andere ingrediënten spelen een rol zoals vormen van vraaggedreven innovatie (vb. overheidsaanbestedingen gericht op innovatie en duurzaamheid), culturele uitwisseling van ‘mindset’ (vb. in Silicon Valley): jonge ondernemers die door bepaalde regio’s worden aangetrokken en nadien opnieuw vertrekken (‘brain circulation’)… Om een metafoor te gebruiken uit het wielrennen: een topregio is zoals een topteam met een vast aantal renners in een ploegentijdrit. Het beste team wordt niet bepaald door de tijd van de eerste renner, maar die van de laatste renner: ook de renners ‘Levenslang Leren’, ‘Ambitieus ondernemen’ … dienen tijdig of zo snel mogelijk de meet te halen om een topprestatie van het team neer te zetten… VARIO benadrukt hier dat indicatoren zorgvuldig dienen te worden geïnterpreteerd. (Nog) hoger scoren op een indicator is bijvoorbeeld niet altijd beter en kan aanleiding geven tot efficiëntiekosten. Volgens Foray & Hollanders (2015) zou geen enkel land of regio er bijvoorbeeld baat bij hebben als heel de bevolking een tertiaire opleiding zou hebben... of als de O&Ointensiteit 50% zou bedragen van het BBP. Het is duidelijk dat er voor de meeste indicatoren een soort van U-vormige performantiecurve bestaat (met een keerpunt), waar bij lage niveaus het de moeite waard is om het prestatieniveau nog te verbeteren, maar dat verdere verbeteringen (na het keerpunt) kunnen leiden tot inefficiënties6. 2. Topinnovatie dient zich ook te vertalen in economisch succes (impact). Zo lijken bijvoorbeeld landen met een bovengemiddeld aandeel in hightechindustrie beter te scoren op veel van de innovatie-indicatoren (EIS2019. VARIO merkt hierbij wel op dat de term ‘hightechindustrie’ met de nodige voorzichtigheid dient worden geïnterpreteerd. Zo is de categorie high-tech (export) gebaseerd op de NACE-codes 21 (Manufacture of basic pharmaceutical products and pharmaceutical preparations) en 26 (Manufacture of computer, electronic and optical products). Dit komt echter niet altijd overeen met de realiteit en is slechts een benaderende indicatie voor hightech (export). In Vlaanderen zijn bijvoorbeeld delen van de textielsector (nieuwe materialen die niet onder de NACE-codes 21 en 26 vallen) ook hightech (vb. technisch of medisch textiel). Deze mismatch geldt echter niet alleen voor Vlaanderen maar ook voor andere landen en regio’s. Zo scoorde China een aantal jaar terug al hoog op deze indicator door loutere assemblage van elektronische componenten. Bijkomende voorzichtigheid in de interpretatie van deze indicator is ook geboden omdat in Vlaanderen de noemer groter is door Zie De Voldere en collega’s (2014) voor een goed overzicht en model van (geavanceerde) economische ontwikkeling. Foray & Hollanders (2015) verwijzen o.a. naar het (te) hoge aantal jonge mensen met een diploma uit het tertiair onderwijs in landen zoals vb. Luxemburg of het hoge aandeel nieuwe doctoraathouders in Zweden of Zwitserland, de (mogelijk te) hoge O&O-intensiteit in Zweden of Zwitserland: “A possible case is the high R&D 5 6

intensities in Finland and Sweden. Although a significant share of these countries’ GDP is spent on R&D activities, per capita income is not among the highest in Europe. One could argue that these countries have been overinvesting in their R&D activities. […] For several countries, the share of their population aged 30–34 years having completed tertiary education might be reaching the above-mentioned turning point. In Ireland, Cyprus, Luxembourg, Finland, Sweden, and Norway, the indicator is already above 45%, and in Switzerland, the 44.2% might also be close to this turning point. [...] A similar argument could be made for new doctorate graduates where Sweden and Switzerland are the only countries with a share above 3%.”

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de doorvoerhandel in zijn havens (Antwerpen, Zeebrugge en Gent). Wallonië scoort bijvoorbeeld beter op deze indicator (o.a. GSK speelt hier een rol in), maar heeft een kleinere noemer mede doordat het geen havens heeft. 3. De meeste Europese topregio’s huisvesten grootstedelijke gebieden. Zij spelen een belangrijke rol in het concurrentievermogen van de regio (cf. supra m.b.t. agglomeratievoordelen). Vertaald naar Vlaanderen betreft het dan bijvoorbeeld de Vlaamse Ruit, Antwerpen (en zijn haven), Lille-Kortrijk-Doornik, Brussels Hoofdstedelijk Gewest7). 4. De kans op een sterke regionale innovatieprestatie stijgt wanneer de regio behoort tot een land dat ook sterk presteert (landen zoals Zwitserland, Denemarken, Zweden…); 5. Topregio’s omarmen de toekomst (vb. 5G, E-commerce, adoptie van AI, duurzaamheid…): “[…]

Being forward-thinking and embracing the future is another key theme for the top players, alongside making technology an integral part of policy. The US, which is second on the overall list, comes top for business dynamism and second for innovation capability”8 6. Innovatie maakt deel uit van het hele economisch systeem: “What really is a differentiating factor is the innovation ecosystem,” […] “Creating the conditions for innovation to become part of the entire economy, not just pockets of excellence. That takes a lot of effort.”9 7.

3.2.

…

Meest relevante benchmarklanden of –regio’s

Op basis van de analyse in Appendix I selecteert VARIO eerst de meest relevante Europese benchmarklanden, vervolgens relevante benchmarkregio’s. 3.2.1. Benchmarklanden Van de Europese landen selecteert VARIO alle EIS-2019-innovatieleiders: Zwitserland, Denemarken, Zweden, Finland en Nederland. Zwitserland is het enige Europese land dat zowel in zijn geheel als met elk van zijn regio’s (NUTS-2) zeer sterke prestaties neerzet. Bovendien situeerden alle zeven Zwitserse regio’s zich consistent in de TOP-25 van RIS over de periode 2011-2019. Van Zwitserland kan Vlaanderen (en met uitbreiding België) in sterke mate leren op systemisch niveau (waaronder op vlak van het interinstitutioneel kader), de mix van maatregelen op federaal en kantonniveau, de beleidsinstrumenten (zoals vb. het ETH-domein van Zürich en Lausanne, fiscaliteit…), historische investeringen en beleidsbeslissingen… Deze hebben geleid tot de uitzonderlijk sterke prestatie van Zwitserland. Het adviestraject van VARIO ‘Naar de topgroep van Kennis- en Innovatieregio’s’ (in prep.) bevat een diepgaande analyse van het Zwitserse O&O&I- en onderwijssysteem.

https://en.wikipedia.org/wiki/List_of_metropolitan_areas_in_Europe Charlton, 2019 9 Charlton, 2019 7

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Naast Zwitserland selecteert VARIO alle andere innovatieleiders uit EIS(2019): Denemarken, Zweden, Finland en Nederland. Ook in EIS(2011) waren deze Scandinavische landen al Innovatieleiders. In EIS(2011) was Nederland nog een innovatievolger (net als België), maar heeft de laatste jaren als runner-up veel vooruitgang geboekt. Nederland is op dit moment een Innovatieleider (EIS2019) en in de Global Competitiveness Index (GCI) 2019 bekleedt Nederland een bijzonder knappe vierde plaats (na Singapore, de VS en Hong Kong). Wat kan Vlaanderen leren van deze recente dynamiek in Nederland? In Appendix II voegen we alle profielen van de geselecteerde landen uit EIS2019 toe, samen met het profiel van België. VARIO merkt nog op dat de race naar kennisen innovatie-economieën op wereldniveau wordt gevoerd (Atkinson & Ezell, 2012). Het adviestraject van VARIO ‘Naar de topgroep van Kennis- en Innovatieregio’s’ (in prep.) bevat daarom ook een diepgaande analyse van Singapore. Deze eilandstaat is sinds 2019 het meest competitieve land ter wereld en heeft de meest open economie. Wat betreft innovatie staat Singapore globaal op een mooie 8 plaats en is het de regionale innovatieleider in Zuidoost-Azië, Oost-Azië en Oceanië (Global Innovation Index 2019). ste

3.2.2. Benchmarkregio’s VARIO selecteert in totaal 17 regio’s uit 6 landen. Uit Zwitserland selecteert VARIO alle NUTS2 regio’s. Een overzicht tonen we in Figuur 2. FIGUUR 2: Innovatieperformantie van Zwitserse Nuts-2 regio’s (RIS2019)

REGIO Région Lémanique (CH01) Espace Mittelland (CH02) Nordwest-schweiz (CH03) Zürich (CH04) Ostschweiz (CH05) Zentralschweiz (CH06) Ticino (CH07)

Bevolkingsdichtheid 152 inw./km2 171 inw./km2 591 inw./km² 870 inw./km² 104 inw./km² 181 inw./km² 126 inw./km²

Bron: RIS2019; Eurostat; Nota: NUTS-2 regio’s zijn vergelijkbaar met de grootte van Belgische provincies.

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RII 140,7 134,8 149,6 160,1 150,2 146,1 156,8

Rang 10 17 7 1 6 8 2

Groep Leader + Leader Leader + Leader + Leader + Leader + Leader +

Naast de NUTS-2 regio’s uit Zwitserland, selecteert VARIO een reeks andere NUTS-2 regio’s uit volgende landen10 die evenzeer sterke prestaties neerzetten: •

• • •

•

Zweden (Innovatieleider in EIS2019): o Stockholm (RIS2019: n°4; RCI2019: n°1) o Sydsverige (RIS2019: n°13; RCI2019: n°24) Denemarken (Innovatieleider in EIS2019): o Hovedstaden (RIS2019: n°5; RCI2019: n°6) Finland (Innovatieleider in EIS2019): o Helsinki-Uusimaa (RIS2019: n°3; RCI2019: n°10) Nederland (Innovatieleider in EIS2019): o Utrecht (RIS2019: n°18; RCI2019: n°3) o Noord-Brabant (RIS2019: n°24; RCI2019: n°20) Duitsland: o Oberbayern (RIS2019: n°11; RCI2019: n°8) o Karlsruhe (RIS2019: n°14; RCI2019: n°15) o Tübingen (RIS2019: n°19; RCI2019: n°23) o Stuttgart (RIS2019: n°23; RCI2019: n°18)

Deze benchmarkregio’s behoren in grote lijnen tot de ‘blauwe banaan’11 (Figuur 3) enerzijds, en de Scandinavische landen (exclusief Noorwegen) anderzijds. Van de Scandinavische regio’s vormen Sydsverige (Malmö) en Hovedstaden (Copenhagen) bovendien de Zweeds-Deense grensoverschrijdende topregio met de bekende Sontbrug12 als fysieke verbinding. FIGUUR 3: De geografisch uitgestrekte stedelijke agglomeratie de Blauwe Banaan waartoe ook Vlaanderen (m.i.v. de Vlaamse Ruit en de EU-metropolen RIJN-Maas en Kortrijk-Rijsel-Doornik) behoort

Bron: https://nl.wikipedia.org/wiki/Blauwe_Banaan, https://nl.wikipedia.org/wiki/Vlaamse_Ruit, https://nl.wikipedia.org/wiki/Euregio_Maas-Rijn en https://nl.wikipedia.org/wiki/Eurometropool_Rijsel-Kortrijk-Doornik Voor Noorwegen ontbreken regionale competitiviteitsindicatoren en staat Noorwegen in de Global Competitiveness Index 2020 “slechts” op een 17de plaats. https://nl.wikipedia.org/wiki/Blauwe_Banaan 12 https://nl.wikipedia.org/wiki/Sontbrug_(Kopenhagen_-_Malm%C3%B6) 10 11

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VARIO stelt vast dat alhoewel Vlaanderen (en België) tot de Blauwe Banaan behoort, we noch België noch Vlaanderen13 op dit moment tot de Europese toplanden/regio’s qua innovatie en competitiviteit kunnen rekenen. Vlaanderen is daarin niet alleen; ook de Franse, Italiaanse en Oostenrijkse deelgebieden binnen de Blauwe Banaan, maar ook Wales behoren niet tot de topregio’s. In Appendix III voegen we de profielen van alle geselecteerde regio’s uit RIS2019 toe, samen met de profielen van het Vlaams Gewest en het Brussels Hoofdstedelijk Gewest.

3.3.

Beperkingen van een benchmarkbenadering: het belang van context

Een benchmarkbenadering heeft beperkingen. De perfecte benchmarkregio of -land bestaat niet. Gezien het beperkt aantal regio’s en landen - er zijn er geen tienduizenden om uit te kiezen - zullen er altijd fundamentele verschillen bestaan tussen Vlaanderen en zijn benchmarkregio’s. We verwijzen o.a. naar (meestal op korte termijn onveranderbare) verschillen14 in economische structuur (vb. eerder B2B of B2C15…), infrastructuur (vb. de aanwezigheid van een grote haven), mate van verstedelijking, historische investeringen en beleidsbeslissingen, democratische bestuursvorm (vb. al dan niet ingebed in FederaalDemocratische unie), het al dan niet hebben van grondstoffen (vb. de gasvelden van Nederland of Noorwegen)… De context van een regio is belangrijk, een goede praktijk (best practice) in het ene land of regio kan niet zondermeer worden getransfereerd naar een ander land of regio. Een zeker pragmatisme en gezond verstand zijn noodzakelijk. VARIO merkt op dat Vlaanderen niet alleen kan leren van succesverhalen, maar tegelijkertijd ook van landen die hierin hebben gefaald16. Bijvoorbeeld, ondanks een gestage groei van zijn O&O-intensiteit van 2,4% (2007) naar 3,16% (2017) (3%-nota, juni 2019), in het kader van een gerichte strategie of roadmap om van Strong Innovator (in 2010) naar Innovation Leader (2020) te gaan, behoort Oostenrijk vandaag (nog) niet tot de innovatieleiders (EIS 2019). Wat kunnen we van deze case leren? Anderzijds is Nederland ondanks een daling van zijn O&O-intensiteit wel opgeklommen van innovatievolger naar innovatieleider. Wat kunnen we leren zowel van de succesverhalen als van de verhalen die minder goed slaagden?

Danielle Raspoet Directeur

Lieven Danneels Voorzitter

Het Brussels Gewest is innovatieleiderAndere relevante factoren zijn uiteraard wel veranderbaar en kan je als regio wel invloed op uitoefenen of stimuleren, zoals innovatiecultuur, (tertiair) onderwijs, de O&O-investeringen, het creëren van een aantrekkelijk vestigingsklimaat… 15 https://jerryrenson.be/kennisbank/b2b-en-b2c-definitie-en-uitleg/ 16 Zie opiniestuk van Frederik Anseel (UNSW Sydney) https://www.tijd.be/opinie/column/het-einde-van-silicon-valley-tours/9917096.html 13 14

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VARIO ADVIES NR. 10 INNOVATIEVE BENCHMARKLANDEN EN -REGIO’S

4. REFERENTIES Ajmone Marsan, G., & Maguire, K. (2011). Categorisation of OECD Regions Using Innovation-Related Variables. OECD Regional Development Working Papers, 2011/03, OECD Publishing. http://dx.doi.org/10.1787/5kg8bf42qv7k-en Atkinson, R. D., & Ezell, S. J. (2012). Innovation Economics: The Race for Global Advantage. Yale University Press. New Haven and London. Charlton, E. (2019). The secrets of the world’s most competitive economies. https://www.weforum.org/agenda/2019/10/the-worlds-most-competitive-economies-global-report/ Cornell University, INSEAD & WIPO (2019). Global Innovation Index 2019: Creating Healthy Lives— The Future of Medical Innovation. Ithaca, Fontainebleau, and Geneva. https://www.wipo.int/publications/en/details.jsp?id=4434 De Voldere, B., Buelens, M., De Stobbeleir, K., Debruyne, M., Meuleman, M., & Sleuwaegen, L. (2014). De inspiratie-economie: een toekomst voor de regionale ontwikkeling van Vlaanderen. Onderzoeksrapport. Flanders DC en Vlerick Business School. Europese Commissie (2011). European Innovation Scoreboard. Luxemburg: Publications office of the European Union. https://op.europa.eu/en/publication-detail/-/publication/705c770c-68f7-4f90-ac2b618cc6cc8ed7/language-en/format-PDF Europese Commissie (2012). Regional Innovation Scoreboard 2011. Luxemburg: Publications office of the European Union. https://op.europa.eu/en/publication-detail/-/publication/aaff75f0-8d26-450396a4-a61a7906d133 Europese Commissie (2019a). Regional Innovation Scoreboard 2019. Luxemburg: Publications office of the European Union. https://ec.europa.eu/growth/industry/innovation/facts-figures/regional_nl Europese Commissie (2019b). The EU Regional Competitiveness Index 2019. Luxemburg: Publications office of the European Union. https://ec.europa.eu/regional_policy/sources/docgener/work/2019_03_rci2019.pdf Europese Commissie (2019c). European Innovation Scoreboard 2019. Luxemburg: Publications office of the European Union. https://ec.europa.eu/docsroom/documents/38781 Foray, D., & Hollanders, H. (2015). An assessment of the innovation union scoreboard as a tool to analyse national innovation capacities: the case of Switzerland. Research evaluation 24, pp. 213-228. doi:10.1093/reseval/rvu036 OESO (2013). Regions and Innovation: Collaborating across Borders. OECD Reviews of Regional innovation. OECD Publishing. http://dx.doi.org/10.1787/9789264205307-en VARIO (in prep.). Naar de Topgroep van Kennis- en Innovatieregio’s.

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WEF (2019). The Global Competitiveness Report 2019. Switzerland: World Economic Forum. http://www3.weforum.org/docs/WEF_TheGlobalCompetitivenessReport2019.pdf

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VARIO ADVIES NR. 10 INNOVATIEVE BENCHMARKLANDEN EN -REGIOâ€™S

APPENDIX I: BENCHMARKANALYSE

VARIO maakte maximaal gebruik van de eerdergenoemde selectiecriteria in Hoofdstuk 2.1. We bekijken hiervoor eerst de indicatoren op landenniveau, vervolgens op regioniveau. Europese benchmarklanden De Europese toplanden wat betreft innovatie (innovatieleiders) zijn volgens EIS2019 (zie FIGUUR A): • • • • •

Zwitserland Zweden Denemarken Finland Nederland

We weerhouden enkel de innovatieleiders uit EIS2019. We merken op dat België in EIS2019 een Strong Innovator is, de categorie onder Innovatieleider.

FIGUUR A: Innovatieleiders in Europees perspectief (EIS2019)

Bron: Europese Commissie, Europees Innovatiescorebord (EIS) 2019

Wat betreft competitiviteit van Europese landen dienen we te kijken naar het recente Global Competitiviteitsrapport 2019 (op wereldniveau) van het Wereld Economisch Forum. Hier zien we dat de 5 innovatieleiders uit EIS ook opduiken in de Wereldtop-20 (Tabel 1). De andere Europese landen in de Top20, Duitsland, het Verenigd Koninkrijk, Frankrijk, Noorwegen en Luxemburg weerhouden we niet omdat ze geen innovatieleider zijn. België staat op positie 22. TABEL 1: Top-20 Landen op Global Competitiveness Index (GCI 2019) RANGORDE 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 … 22

LAND Singapore VS Hong Kong Nederland Zwitserland Japan Duitsland Zweden Verenigd Koninkrijk Denemarken Finland Taiwan Zuid-Korea Canada Frankrijk Australië Noorwegen Luxemburg Nieuw-Zeeland Israël … België

GCI-SCORE 84,4 83,7 83,1 82,4 82,3 82,3 81,8 81,2 81,2 81,2 80,2 80,2 79,6 79,6 78,8 78,7 78,1 77,0 76,7 76,7 … 76,4

Bron: GCI 2019

Conclusie: we selecteren de EIS-2019-Innovatieleiders, die ook behoren tot de GCI-2019-Top20, zijnde: • • • • •

Zwitserland Zweden Denemarken Finland Nederland

Europese Benchmarkregioâ€™s Om de Europese topregioâ€™s te vinden, kunnen we kijken naar en RIS2019 (FIGUUR B) en RCI2019 (FIGUUR C). Het Vlaams Gewest bevindt zich in RIS2019 op plaats 40 in de categorie Stong Innovator+.

FIGUUR B: Regionale innovatieprestaties in Europees perspectief (RIS2019)

Bron: Europese Commissie, Regionaal Innovatiescorebord 2019

FIGUUR C: Regionale competitiviteit in Europees perspectief (RCI, 2019)

Bron: Europese Commissie, Regional Competitiveness Index â€“ RCI 2019 Nota: gegevens voor Zwitserse en Noorse regioâ€™s ontbreken

TABEL 2: Top 25 Regionale Innovatieleiders (RIS 2019) 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15

REGIO Zürich Ticino Helsinki-Uusimaa Stockholm Hovedstaden Ostschweiz Nordwestschweiz Zentralschweiz Berlin Région lémanique Oberbayern Västsverige Sydsverige Karlsruhe Trøndelag

LAND Zwitserland Zwitserland Finland Zweden Denemarken Zwitserland Zwitserland Zwitserland Duitsland Zwitserland Duitsland Zweden Zweden Duitsland Noorwegen

Oslo og Akershus

Noorwegen

17 18

Espace Mittelland Utrecht

Zwitserland Nederland

19 20 21

Tübingen Östra Mellansverige Braunschweig

Duitsland Zweden Duitsland

South East

Verenigd Koninkrijk

23 24

Stuttgart Noord-Brabant

Duitsland Nederland

Mittelfranken … Vlaams Gewest

Duitsland … België

Rang (2011) 1 12 9 4 3 14 2 5 20 11 7 16 6 8 <25 (top25 sinds 2015) <25 (top25 sinds 2017) 22 <25 (top25 sinds 2013) 10 13 <25 (eenmaal top25 in 2013) <25 (top25 sinds 2017) 15 <25 (tweemaal top25 in 2013 en 2015) 19 Innovation Leader (Medium)

Bron: RIS2019 Nota: Enkel Innovation Leaders+ en Innovation Leaders (11% sterkst presterende regio’s van in totaal 238 regio’s) worden getoond. De Innovation Leaders- (waaronder BHG) worden niet weergegeven in de tabel.

TABEL 3: Top-25 meest competitieve regio’s (RCI 2019) 1 2

3 4 5 6 7 8 9 10 11 12 13 15 17 18 19 20 22 23 24 25

REGIO Stockholm London & its commuting zones (Inner London West & Inner London East & Outer London East-North-East & Outer London West North West & Bedfroshire/Hertfordshire & Essex) Utrecht Berkshire, Buckinghamshire and Oxfordshire Surrey, East and West Sussex Hovedstaden Luxembourg Oberbayern Amsterdam & its commuting zones (Flevoland&Noord-Holland) Helsinki-Uusimaa Île de France Hamburg Darmstadt Zuid-Holland Karlsruhe Hampshire and Isle of Wight Cheshire Stuttgart Köln Gelderland Noord-Brabant Gloucestershire, Wiltshire & Bristol/Bath area Tübingen Sydsverige Brussels & its commuting zones (Vlaams &Waals Brabant)

… 29 … 31 … 56 … 63

Antwerpen … Oost-Vlaanderen … Limburg … West-Vlaanderen

LAND Zweden

Verenigd Koninkrijk

Nederland Verenigd Koninkrijk Verenigd Koninkrijk Denemarken Luxemburg Duitsland Nederland Finland Frankrijk Duitsland Duitsland Nederland Duitsland Verenigd Koninkrijk Verenigd Koninkrijk Duitsland Duitsland Nederland Nederland Verenigd Koninkrijk Duitsland Zweden België

België … België … België … België

Bron: RCI2019; 268 regio’s Nota: gegevens voor Noorwegen of Zwitserland werden niet meegenomen in RCI2019; In GCI2019 staat Zwitserland als land op plaats 5.

Op basis van Tabel 2 en Tabel 3 en de selectiecriteria (in Hoofdstuk 2.1.), worden in totaal zeventien benmarkregio’s (Tabel 4) weerhouden: uit Zwitserland (alle zeven regio’s), Denemarken (1 regio), Finland (1 regio), Zweden (2 regio’s), Duitsland (4 regio’s) en Nederland (2 regio’s).

TABEL 4: Zeventien weerhouden benchmarkregio’s o.b.v. selectiecriteria uitgevoerd op Tabel 2 en 3

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17

REGIO

LAND

NUTS (grootte van de regio)

Zürich Ticino Helsinki-Uusimaa Stockholm Hovedstaden Ostschweiz Nordwestschweiz Zentralschweiz Région lémanique Oberbayern Sydsverige Karlsruhe Espace Mittelland Utrecht Tübingen Stuttgart Noord-Brabant

Zwitserland Zwitserland Finland Zweden Denemarken Zwitserland Zwitserland Zwitserland Zwitserland Duitsland Zweden Duitsland Zwitserland Nederland Duitsland Duitsland Nederland

2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2

Bevolkingsdichtheid (inw./km²) 870 126 181 351 745 104 591 181 152 270 108 406 171 918 212 390 508

1 2 2 2 2 2 1/2 -

487 380 508 648 361 544 7422 820

Vlaams Gewest West-Vlaanderen Oost-Vlaanderen Antwerpen Limburg Vlaams-Brabant Brussels Hoofdstedelijk Gewest Vlaamse ruit Bron: RCI2019, RIS2019; Wikipedia

Nota: Voor NUTS-classificatie zie: https://nl.wikipedia.org/wiki/Nomenclatuur_van_territoriale_eenheden_voor_de_statistiek

Alle weerhouden regio’s bevinden zich op NUTS-2 niveau (qua grootte vergelijkbaar met Belgische provincies) en vallen onder de leidende innovatielanden in EIS2019, samen met de vier NUTS-2 regio’s uit Duitsland. We merken op dat in de top25 van RCI2019 ook heel wat sterk competitieve regio’s uit het Verenigd Koninkrijk voorkomen. In RIS2019 komt er echter slechts 1 Britse regio voor (South East), dat pas sinds 2017 in de top 25 van het Regionale Innovatie Scoreboard voorkomt en daardoor niet weerhouden werd. Een aantal Duitse (Braunschweig, Berlijn) en Zweedse regio’s (Västsverige, Östra Mellansverige) komen wel voor in de top25 van RIS2019 maar niet in de top25 van RCI2019 of omgekeerd

en werden daardoor niet weerhouden. Bovendien is Berlijn als city-succes regio te beschouwen en daardoor ook niet vergelijkbaar met Vlaanderen. De meeste topregio’s (zie Tabel 2 en Tabel 3) uit Nederland, Zwitserland, Duitsland en het Verenigd Koninkrijk volgen niet toevallig de bekende, uitgestrekte stedelijke agglomeratie de Blauwe Banaan (FIGUUR D), een Europese megalopolis, met meer dan 85 miljoen inwoners1. We stellen vast dat alhoewel Vlaanderen (en België) tot de Blauwe Banaan behoort, we Vlaanderen2 op dit moment nog niet tot de Europese toplanden of regio’s qua innovatie en competitiviteit kunnen rekenen. Vlaanderen is daarin niet alleen; ook de Franse, Italiaanse en Oostenrijkse deelgebieden binnen de Blauwe Banaan, maar ook Wales behoren niet tot de topregio’s. In RCI2019 staat enkel het Brussels Hoofdstedelijk Gewest met de woon-werkzones (commuting zones) Vlaams en Waals Brabant, in de top25 (plaats 25).

FIGUUR D: De Vlaamse Ruit, de EU-regio Kortrijk-Rijsel-Doornik en de EU-Regio Rijn-Maas als onderdelen van de geografisch veel uitgestrektere stedelijke agglomeratie de Blauwe Banaan

1 2

https://nl.wikipedia.org/wiki/Blauwe_Banaan Het Brussels Hoofdstedelijk Gewest is Innovatieleider-

APPENDIX II: PROFIELEN VAN BENCHMARKLANDEN EN BELGIÃ‹

European Innovation Scoreboard 2019

Belgium is a Strong Innovator. Over time, performance has increased relative to that of the EU in 2011.

180 160 140 120

116

117

121

124

100

128

Linkages, Innovators and Attractive research systems, are the strongest innovation dimensions. Belgium scores particularly well on Innovative SMEs collaborating with others, International scientific co-publications, and Enterprises providing ICT training. Employment impacts and Intellectual assets are the weakest innovation dimensions. Overall, Belgium scores weakest on Employment fast-growing enterprises of innovative sectors, Opportunity-driven entrepreneurship, and Non-R&D innovation expenditures.

118

Structural differences with the EU are shown in the table below. Top R&D spending enterprises per 10 million population are well above the EU average, whereas the turnover share of large enterprises, FDI net inflows, and enterprise births are well below the EU average.

60 40 20 0 2011 2012 2013 2014 2015 2016 2017 2018 Relative to EU in 2011

Relative to EU in 2018

Belgium SUMMARY INNOVATION INDEX Human resources New doctorate graduates Population with tertiary education Lifelong learning Attractive research systems International scientific co-publications Most cited publications Foreign doctorate students Innovation-friendly environment Broadband penetration Opportunity-driven entrepreneurship Finance and support R&D expenditure in the public sector Venture capital expenditures Firm investments R&D expenditure in the business sector Non-R&D innovation expenditures Enterprises providing ICT training Innovators SMEs product/process innovations SMEs marketing/organizational innovations SMEs innovating in-house Linkages Innovative SMEs collaborating with others Public-private co-publications Private co-funding of public R&D exp. Intellectual assets PCT patent applications Trademark applications Design applications Employment impacts Employment in knowledge-intensive activities Employment fast-growing enterprises Sales impacts Medium and high-tech product exports Knowledge-intensive services exports Sales of new-to-market/firm innovations

Relative to EU 2018 in 2018 117.7 106.1 94.2 143.1 75.5 128.5 176.3 116.6 187.4 106.4 161.1 48.9 108.3 130.3 89.7 119.6 130.0 62.1 168.4 148.8 148.9 137.6 159.4 157.7 196.5 148.4 130.9 89.7 98.1 104.6 66.3 76.4 116.5 45.2 100.1 79.2 100.6 127.0

Performance relative to EU 2011 in 2011 2018 116.3 128.1 115.1 129.7 100.0 136.7 163.4 170.9 77.1 77.1 147.9 144.7 189.8 256.4 127.2 127.7 152.6 179.2 173.0 168.2 177.8 322.2 169.8 63.3 95.5 118.4 90.7 120.5 101.1 115.9 123.0 142.6 116.3 148.9 83.5 72.6 173.3 213.3 130.7 135.2 132.5 144.6 114.1 117.5 145.7 143.5 151.6 163.8 210.9 209.8 142.2 174.2 112.2 125.7 97.8 87.2 94.4 89.3 108.7 116.6 92.2 61.1 74.7 79.8 126.9 126.9 36.9 45.8 81.1 103.1 80.8 85.4 97.4 103.8 62.8 123.2

The colours show normalised performance in 2018 relative to that of the EU in 2018: dark green: above 120%; light green: between 90% and 120%; yellow: between 50% and 90%; orange: below 50%. Normalised performance uses the data after a possible imputation of missing data and transformation of the data.

BE Performance and structure of the economy GDP per capita (PPS) Average annual GDP growth (%) Employment share manufacturing (NACE C) (%) of which High and medium high-tech (%) Employment share services (NACE G-N) (%) of which Knowledge-intensive services (%) Turnover share SMEs (%) Turnover share large enterprises (%) Foreign-controlled enterprises â€“ share of value added (%) Business and entrepreneurship Enterprise births (10+ employees) (%) Total Entrepreneurial Activity (TEA) (%) FDI net inflows (% GDP) Top R&D spending enterprises per 10 million population Buyer sophistication (1 to 7 best) Governance and policy framework Ease of starting a business (0 to 100 best) Basic-school entrepren. education and training (1 to 5 best) Govt. procurement of advanced tech products (1 to 7 best) Rule of law (-2.5 to 2.5 best) Demography Population size (millions) Average annual population growth (%) Population density (inhabitants/km2)

34,600 29,500 1.5 2.2 12.6 15.5 35.1 37.5 40.2 41.8 36.5 35.0 39.8 37.9 35.7 44.4 13.1 12.6 0.6 6.2 2.1 29.2 4.4

1.5 6.7 4.3 19.6 3.7

71.9 2.0 3.5 1.4

76.8 1.9 3.5 1.2

11.4 0.4 373.0

511.3 0.2 117.5

EU targets for 2020 Indicator Gross domestic expenditure on R&D (% of GDP) Tertiary educational attainment (% of population aged 30-34)

2014 2.39 43.8

Latest Target1 2.58 3.00 47.6

47.0

1 Sources are provided in the introduction to the country profiles.

European Semester country report and country specific recommendations: https://rio.jrc.ec.europa.eu/en/library/research-and-innovation-analysis-europeansemester-2019-country-reports https://rio.jrc.ec.europa.eu/en/library/country-specific-recommendations-2019research-and-innovation-analysis

European Innovation Scoreboard 2019

Denmark is an Innovation Leader. Over time, performance has remained the same compared to that of the EU in 2011. 200 180 160 140 120 100 80 60 40 20 0

141

143

145

143

140

141

Attractive research systems, Innovation-friendly environment and Human resources are the strongest innovation dimensions. Denmark scores particularly well on Public-private co-publications, International scientific co-publications, and Lifelong learning. Sales impacts and Innovators are the weakest innovation dimensions. Overall, Denmarkâ€™s lowest indicator scores comprise Sales of new-to-market and new-to-firm product innovations, Non-R&D innovation expenditures, and Venture capital expenditures.

130

Structural differences with the EU are shown in the table below. GDP per capita and top R&D spending enterprises per 10 million population are well above the EU average. Enterprise births and FDI net inflows are well below the EU average. 2011 2012 2013 2014 2015 2016 2017 2018 Relative to EU in 2011

Relative to EU in 2018

Denmark SUMMARY INNOVATION INDEX Human resources New doctorate graduates Population with tertiary education Lifelong learning Attractive research systems International scientific co-publications Most cited publications Foreign doctorate students Innovation-friendly environment Broadband penetration Opportunity-driven entrepreneurship Finance and support R&D expenditure in the public sector Venture capital expenditures Firm investments R&D expenditure in the business sector Non-R&D innovation expenditures Enterprises providing ICT training Innovators SMEs product/process innovations SMEs marketing/organizational innovations SMEs innovating in-house Linkages Innovative SMEs collaborating with others Public-private co-publications Private co-funding of public R&D exp. Intellectual assets PCT patent applications Trademark applications Design applications Employment impacts Employment in knowledge-intensive activities Employment fast-growing enterprises Sales impacts Medium and high-tech product exports Knowledge-intensive services exports Sales of new-to-market/firm innovations

Relative to EU 2018 in 2018 129.5 180.4 157.2 143.1 262.2 183.8 265.1 143.5 174.0 182.3 177.8 187.0 106.7 174.7 49.1 104.5 145.7 45.3 126.3 95.7 96.1 114.2 77.5 139.2 109.8 315.1 70.5 163.8 175.1 142.6 173.2 100.7 110.6 93.0 75.3 79.8 112.8 23.7

Performance relative to EU 2011 in 2011 2018 140.7 140.9 192.5 220.6 146.2 228.3 167.2 170.9 267.7 267.7 160.0 207.0 257.0 385.6 144.1 157.1 120.2 166.4 244.6 288.1 266.7 355.6 229.6 242.2 128.2 116.7 141.1 161.6 112.9 63.5 119.7 124.6 166.1 166.9 45.9 52.9 153.3 160.0 103.4 86.9 109.1 93.3 100.2 97.5 100.9 69.8 175.5 144.6 215.5 117.2 349.3 369.7 71.5 67.7 152.4 159.3 171.7 159.3 135.2 158.9 146.5 159.7 127.3 105.1 120.5 120.5 132.1 94.0 91.2 77.6 68.1 86.1 123.1 116.4 82.0 22.9

DK Performance and structure of the economy GDP per capita (PPS) Average annual GDP growth (%) Employment share manufacturing (NACE C) (%) of which High and medium high-tech (%) Employment share services (NACE G-N) (%) of which Knowledge-intensive services (%) Turnover share SMEs (%) Turnover share large enterprises (%) Foreign-controlled enterprises â€“ share of value added (%) Business and entrepreneurship Enterprise births (10+ employees) (%) Total Entrepreneurial Activity (TEA) (%) FDI net inflows (% GDP) Top R&D spending enterprises per 10 million population Buyer sophistication (1 to 7 best) Governance and policy framework Ease of starting a business (0 to 100 best) Basic-school entrepreneurial education and training (1 to 5 best) Govt. procurement of advanced tech products (1 to 7 best) Rule of law (-2.5 to 2.5 best) Demography Population size (millions) Average annual population growth (%) Population density (inhabitants/km2)

37,400 29,500 1.8 2.2 11.8 15.5 42.9 37.5 41.4 41.8 34.8 35.0 40.7 37.9 40.7 44.4 10.6 12.6 0.5 n/a 1.3 63.1 3.7

1.5 6.7 4.3 19.6 3.7

84.0

76.8

n/a

1.9

3.5 1.9

3.5 1.2

5.7 0.6 135.4

511.3 0.2 117.5

EU targets for 2020 Indicator Gross domestic expenditure on R&D (% of GDP) Tertiary educational attainment (% of population aged 30-34)

2014 2.91

Latest 3.05

Target1 3.00

44.9

49.1

40.0

1 Sources are provided in the introduction to the country profiles.

European Innovation Scoreboard 2019

The Netherlands is an Innovation Leader. Over time, performance has increased relative to that of the EU in 2011.

200 180 160 140 120 100 80 60 40 20 0

119

126

128

126

127

129

134

135

Attractive research systems, Innovation-friendly environment and Linkages are the strongest innovation dimensions. The Netherlands scores particularly well on Foreign doctorate students, International scientific co-publications, and Public-private co-publications. Firm investments and Sales impacts are the weakest innovation dimensions. Overall, the Netherlandsâ€™ lowest indicator scores comprise Non-R&D innovation expenditures, Sales of new-to-market and new-to-firm product innovations, and Medium and high-tech product exports.

124

2011 2012 2013 2014 2015 2016 2017 2018 Relative to EU in 2011

Relative to EU in 2018

Relative to EU 2018 in 2018 SUMMARY INNOVATION INDEX 124.0 Human resources 142.1 New doctorate graduates 107.9 Population with tertiary education 148.1 Lifelong learning 183.7 Attractive research systems 170.0 International scientific co-publications 191.8 Most cited publications 142.5 Foreign doctorate students 197.4 Innovation-friendly environment 166.6 Broadband penetration 172.2 Opportunity-driven entrepreneurship 160.7 Finance and support 118.4 R&D expenditure in the public sector 128.3 Venture capital expenditures 110.0 Firm investments 71.2 R&D expenditure in the business sector 85.8 Non-R&D innovation expenditures 13.9 Enterprises providing ICT training 115.8 Innovators 125.7 SMEs product/process innovations 153.3 SMEs marketing/organizational innovations 84.0 SMEs innovating in-house 135.4 Linkages 143.5 Innovative SMEs collaborating with others 124.5 Public-private co-publications 187.1 Private co-funding of public R&D exp. 136.1 Intellectual assets 124.3 PCT patent applications 156.5 Trademark applications 117.4 Design applications 98.2 Employment impacts 113.8 Employment in knowledge-intensive activities 134.1 Employment fast-growing enterprises 98.0 Sales impacts 92.7 Medium and high-tech product exports 82.6 Knowledge-intensive services exports 118.9 Sales of new-to-market/firm innovations 74.0 Netherlands

Performance relative to EU 2011 in 2011 2018 118.9 135.0 152.8 173.7 130.8 156.7 153.0 176.9 175.0 187.5 172.4 191.4 198.4 279.0 154.5 156.0 183.1 188.7 196.4 263.4 166.7 344.4 216.7 208.2 107.2 129.4 122.4 118.7 89.2 142.2 81.9 84.9 88.8 98.3 77.0 16.2 80.0 146.7 76.8 114.1 87.0 148.8 61.5 71.7 81.9 122.0 149.0 149.1 118.0 132.9 227.8 219.5 137.8 130.6 120.2 120.8 149.5 142.3 124.0 130.8 86.7 90.5 120.5 118.8 146.2 146.2 102.0 99.1 84.3 95.5 71.2 89.1 122.0 122.7 56.4 71.8

Structural differences with the EU are shown in the table below. The Netherlands scores high on various economic indicators. GDP per capita, the turnover share of SMEs, total entrepreneurial activity, FDI net inflows, and top R&D spending enterprises per 10 million population are well above the EU average. The employment share in high and medium high-tech manufacturing and enterprise births are well below the EU average.

Performance and structure of the economy GDP per capita (PPS) 37,900 29,500 Average annual GDP growth (%) 2.7 2.2 Employment share manufacturing (NACE C) (%) 10.3 15.5 of which High and medium high-tech (%) 30.3 37.5 Employment share services (NACE G-N) (%) 46.5 41.8 of which Knowledge-intensive services (%) 39.6 35.0 Turnover share SMEs (%) 47.7 37.9 Turnover share large enterprises (%) 37.3 44.4 Foreign-controlled enterprises â€“ share of value added (%) 13.5 12.6 Business and entrepreneurship Enterprise births (10+ employees) (%) 0.9 1.5 Total Entrepreneurial Activity (TEA) (%) 11.1 6.7 FDI net inflows (% GDP) 27.7 4.3 Top R&D spending enterprises per 10 million population 29.0 19.6 Buyer sophistication (1 to 7 best) 4.4 3.7 Governance and policy framework Ease of starting a business (0 to 100 best) 75.7 76.8 Basic-school entrepren. education and training (1 to 5 best) 3.3 1.9 Govt. procurement of advanced tech products (1 to 7 best) 4.0 3.5 Rule of law (-2.5 to 2.5 best) 1.9 1.2 Demography Population size (millions) 17.1 511.3 Average annual population growth (%) 0.6 0.2 Population density (inhabitants/km2) 500.8 117.5 EU targets for 2020 Indicator Gross domestic expenditure on R&D (% of GDP) Tertiary educational attainment (% of population aged 30-34)

2014 1.98

Latest 1.99

Target1 2.50

44.8

49.4

40.0

1 Sources are provided in the introduction to the country profiles.

European Innovation Scoreboard 2019

200 180 160 140 120 100 80 60 40 20 0

Finland is an Innovation Leader. Over time, performance has increased relative to that of the EU in 2011. The strong increase in 2018 is almost entirely explained by improved performance on the indicators using CIS data.

132

129

132

133

135

146 134

Innovation-friendly environment, Innovators and Human resources are the strongest innovation dimensions. Performance on Lifelong learning, PCT patent applications, and International scientific co-publications is well above the EU average. Employment impacts and Sales impacts are the weakest innovation dimensions. Finlandâ€™s lowest indicator scores are on Employment fast-growing enterprises of innovative sectors, Medium and high-tech product exports, and Venture capital expenditures.

Structural differences with the EU are shown in the table below. All indicators are close to the EU average, except for the share of enterprise births, which is well below the EU average, and top R&D spending enterprises per 10 million population, which is well above the EU average.

2011 2012 2013 2014 2015 2016 2017 2018 Relative to EU in 2011

Relative to EU in 2018

Relative to EU 2018 in 2018 SUMMARY INNOVATION INDEX 134.0 Human resources 157.0 New doctorate graduates 128.8 Population with tertiary education 102.5 Lifelong learning 268.4 Attractive research systems 135.4 International scientific co-publications 202.8 Most cited publications 112.8 Foreign doctorate students 107.8 Innovation-friendly environment 182.3 Broadband penetration 177.8 Opportunity-driven entrepreneurship 187.0 Finance and support 113.6 R&D expenditure in the public sector 152.5 Venture capital expenditures 80.6 Firm investments 129.8 R&D expenditure in the business sector 133.0 Non-R&D innovation expenditures 88.9 Enterprises providing ICT training 168.4 Innovators 168.2 SMEs product/process innovations 174.9 SMEs marketing/organizational innovations 136.6 SMEs innovating in-house 191.1 Linkages 152.0 Innovative SMEs collaborating with others 189.1 Public-private co-publications 202.2 Private co-funding of public R&D exp. 95.3 Intellectual assets 151.8 PCT patent applications 219.4 Trademark applications 137.1 Design applications 97.5 Employment impacts 80.2 Employment in knowledge-intensive activities 123.5 Employment fast-growing enterprises 46.5 Sales impacts 85.4 Medium and high-tech product exports 67.5 Knowledge-intensive services exports 106.6 Sales of new-to-market/firm innovations 83.1 Finland

Performance relative to EU 2011 in 2011 2018 131.6 145.9 176.8 192.0 184.6 187.0 123.1 122.4 228.1 274.0 108.6 152.5 199.4 295.0 107.9 123.5 49.0 103.1 161.2 288.1 222.2 355.6 119.6 242.2 158.5 124.2 161.6 141.1 154.8 104.3 174.1 154.7 220.2 152.4 83.5 103.8 226.7 213.3 111.2 152.7 124.5 169.8 71.3 116.6 138.2 172.1 158.1 157.9 141.4 201.9 234.6 237.2 137.3 91.5 142.4 147.6 212.8 199.5 115.4 152.7 91.8 89.9 86.4 83.7 121.8 134.6 60.8 47.0 80.2 88.0 67.2 72.9 56.4 109.9 123.1 80.6

Performance and structure of the economy GDP per capita (PPS) 32,100 29,500 Average annual GDP growth (%) 2.5 2.2 Employment share manufacturing (NACE C) (%) 13.4 15.5 of which High and medium high-tech (%) 36.1 37.5 Employment share services (NACE G-N) (%) 40.0 41.8 of which Knowledge-intensive services (%) 39.3 35.0 Turnover share SMEs (%) 40.1 37.9 Turnover share large enterprises (%) 44.3 44.4 Foreign-controlled enterprises â€“ share of value added (%) 9.5 12.6 Business and entrepreneurship Enterprise births (10+ employees) (%) 0.4 1.5 Total Entrepreneurial Activity (TEA) (%) 6.7 6.7 FDI net inflows (% GDP) 4.9 4.3 Top R&D spending enterprises per 10 million population 67.4 19.6 Buyer sophistication (1 to 7 best) 4.6 3.7 Governance and policy framework Ease of starting a business (0 to 100 best) 80.4 76.8 Basic-school entrepren. education and training (1 to 5 best) 2.4 1.9 Govt. procurement of advanced tech products (1 to 7 best) 3.9 3.5 Rule of law (-2.5 to 2.5 best) 2.0 1.2 Demography Population size (millions) 5.5 511.3 Average annual population growth (%) 0.2 0.2 Population density (inhabitants/km2) 18.1 117.5 EU targets for 2020 Indicator Gross domestic expenditure on R&D (% of GDP) Tertiary educational attainment (% of population aged 30-34)

2014 3.17

Latest 2.76

Target1 4.00

45.3

44.2

42.0

1 Sources are provided in the introduction to the country profiles.

European Innovation Scoreboard 2019

Sweden is an Innovation Leader. Over time, performance has increased relative to that of the EU in 2011.

200 180 160 140 120 100 80 60 40 20 0

143

145

146

144

145

148

148 136

Human resources, Innovation-friendly environment and Attractive research systems are the strongest innovation dimensions. Sweden scores high on Public-private co-publications, Lifelong learning, and International scientific co-publications. Sales impacts is the weakest innovation dimension. Low-scoring indicators include Sales of newto-market and new-to-firm product innovations, Venture capital expenditures, and Private co-funding of public R&D expenditure.

Structural differences with the EU are shown in the table below. GDP per capita and top R&D spending enterprises per 10 million population are well above the EU average. The employment share in manufacturing, enterprise births, and FDI net inflows are well below the EU average.

2011 2012 2013 2014 2015 2016 2017 2018 Relative to EU in 2011

Relative to EU in 2018

Sweden SUMMARY INNOVATION INDEX Human resources New doctorate graduates Population with tertiary education Lifelong learning Attractive research systems International scientific co-publications Most cited publications Foreign doctorate students Innovation-friendly environment Broadband penetration Opportunity-driven entrepreneurship Finance and support R&D expenditure in the public sector Venture capital expenditures Firm investments R&D expenditure in the business sector Non-R&D innovation expenditures Enterprises providing ICT training Innovators SMEs product/process innovations SMEs marketing/organizational innovations SMEs innovating in-house Linkages Innovative SMEs collaborating with others Public-private co-publications Private co-funding of public R&D exp. Intellectual assets PCT patent applications Trademark applications Design applications Employment impacts Employment in knowledge-intensive activities Employment fast-growing enterprises Sales impacts Medium and high-tech product exports Knowledge-intensive services exports Sales of new-to-market/firm innovations

Relative to EU 2018 in 2018 135.8 174.9 133.2 149.4 268.4 166.2 239.2 121.0 173.7 172.3 177.8 166.6 109.3 158.5 67.5 124.3 179.4 92.4 105.3 115.4 115.1 102.8 127.8 147.3 112.8 314.5 87.4 156.2 234.0 132.5 100.4 134.5 150.6 122.0 88.0 94.9 106.2 56.6

Performance relative to EU 2011 in 2011 2018 143.4 147.7 205.0 213.9 207.7 193.4 165.7 178.4 245.8 274.0 151.5 187.2 241.4 347.9 125.3 132.5 132.7 166.1 232.7 272.4 244.4 355.6 224.7 215.7 141.8 119.5 154.2 146.7 127.2 87.3 138.7 148.1 187.5 205.6 104.0 107.9 126.7 133.3 113.3 104.8 119.9 111.7 89.1 87.7 131.0 115.0 155.5 153.0 153.5 120.4 306.5 369.0 92.0 83.8 149.8 151.9 212.8 212.8 126.3 147.6 103.7 92.6 136.9 140.5 143.6 164.1 132.0 123.4 91.7 90.6 100.1 102.4 111.1 109.6 59.5 54.9

Performance and structure of the economy GDP per capita (PPS) 36,100 29,500 Average annual GDP growth (%) 2.2 2.2 Employment share manufacturing (NACE C) (%) 10.3 15.5 of which High and medium high-tech (%) 42.5 37.5 Employment share services (NACE G-N) (%) 41.3 41.8 of which Knowledge-intensive services (%) 44.0 35.0 Turnover share SMEs (%) 38.4 37.9 Turnover share large enterprises (%) 43.0 44.4 Foreign-controlled enterprises â€“ share of value added (%) 13.5 12.6 Business and entrepreneurship Enterprise births (10+ employees) (%) 0.4 1.5 Total Entrepreneurial Activity (TEA) (%) 7.2 6.7 FDI net inflows (% GDP) 3.0 4.3 Top R&D spending enterprises per 10 million population 81.8 19.6 Buyer sophistication (1 to 7 best) 4.6 3.7 Governance and policy framework Ease of starting a business (0 to 100 best) 81.1 76.8 Basic-school entrepren. education and training (1 to 5 best) 2.4 1.9 Govt. procurement of advanced tech products (1 to 7 best) 4.0 3.5 Rule of law (-2.5 to 2.5 best) 2.0 1.2 Demography Population size (millions) 10.0 511.3 Average annual population growth (%) 1.4 0.2 Population density (inhabitants/km2) 24.4 117.5 EU targets for 2020 Indicator Gross domestic expenditure on R&D (% of GDP) Tertiary educational attainment (% of population aged 30-34)

2014 3.14

Latest 3.40

Target1 4.00

49.9

52.0

45.0

1 Sources are provided in the introduction to the country profiles.

European Innovation Scoreboard 2019

Switzerland is an Innovation Leader. Over time, performance has increased relative to that of the EU in 2011.

200 180 160 140 120 100 80 60 40 20 0

161

158

159

161

163

166

168

171

Attractive research systems, Human resources and Firm investments are the strongest innovation dimensions. Switzerland scores particularly well on Public-private co-publications, Foreign doctorate students, and Lifelong learning. Employment impacts and Sales impacts are the weakest innovation dimensions. Overall, Switzerland’s lowest indicator scores comprise Employment fast-growing enterprises of innovative sectors, Innovative SMEs collaborating with others, and Medium and high-tech product exports.

157

2011 2012 2013 2014 2015 2016 2017 2018 Relative to EU in 2011

Structural differences with the EU are shown in the table below. For several indicators data are not available. Many economic indicators are well above the EU average, including GDP per capita, the employment share in knowledge-intensive services, FDI net inflows, top R&D spending enterprises per 10 million population, and buyer sophistication. However, enterprise births is well below the EU average.

Relative to EU in 2018

Relative to EU 2018 Switzerland in 2018 SUMMARY INNOVATION INDEX 156.7 Human resources 195.5 New doctorate graduates 170.7 Population with tertiary education 166.9 Lifelong learning 268.4 Attractive research systems 207.9 International scientific co-publications 265.1 Most cited publications 141.9 Foreign doctorate students 268.8 Innovation-friendly environment § 147.0 Broadband penetration N/A Opportunity-driven entrepreneurship 150.8 Finance and support 134.9 R&D expenditure in the public sector 150.5 Venture capital expenditures 121.8 Firm investments § 175.0 R&D expenditure in the business sector 177.1 Non-R&D innovation expenditures 176.1 Enterprises providing ICT training N/A Innovators 157.2 SMEs product/process innovations 139.3 SMEs marketing/organizational innovations 190.5 SMEs innovating in-house 144.7 Linkages 158.6 Innovative SMEs collaborating with others 79.6 Public-private co-publications 315.1 Private co-funding of public R&D exp. 140.5 Intellectual assets 173.4 PCT patent applications 191.1 Trademark applications 186.4 Design applications 142.4 Employment impacts 112.3 Employment in knowledge-intensive activities 184.7 Employment fast-growing enterprises 55.9 Sales impacts 115.8 Medium and high-tech product exports 88.5 Knowledge-intensive services exports 102.5 Sales of new-to-market/firm innovations 167.9

Performance relative to EU 2011 in 2011 2018 161.4 170.6 229.3 239.0 269.2 247.9 152.2 199.3 274.0 274.0 226.1 234.2 385.6 385.6 157.1 155.4 228.4 257.1 175.4 232.4 N/A N/A 147.5 195.3 84.7 147.6 105.6 139.2 60.0 157.5 172.6 208.7 193.6 203.0 146.1 205.6 N/A N/A 143.7 142.8 169.8 135.2 170.0 162.6 90.7 130.3 163.8 164.7 82.2 85.0 369.7 369.7 134.8 134.8 187.5 168.6 188.6 173.8 223.8 207.6 156.7 131.3 106.9 117.2 175.6 201.3 57.3 56.6 130.6 119.2 125.7 95.5 97.5 105.7 174.5 162.9

Performance and structure of the economy GDP per capita (PPS) 47,200 29,500 Average annual GDP growth (%) 2.1 2.2 Employment share manufacturing (NACE C) (%) 12.9 15.5 of which High and medium high-tech (%) 44.6 37.5 Employment share services (NACE G-N) (%) 45.1 41.8 of which Knowledge-intensive services (%) 45.7 35.0 Turnover share SMEs (%) n/a 37.9 Turnover share large enterprises (%) n/a 44.4 Foreign-controlled enterprises – share of value added (%) n/a 12.6 Business and entrepreneurship Enterprise births (10+ employees) (%) 0.2 1.5 Total Entrepreneurial Activity (TEA) (%) 8.0 6.7 FDI net inflows (% GDP) 10.6 4.3 Top R&D spending enterprises per 10 million population 67.6 19.6 Buyer sophistication (1 to 7 best) 5.0 3.7 Governance and policy framework Ease of starting a business (0 to 100 best) 75.6 76.8 Basic-school entrepren. education and training (1 to 5 best) 2.2 1.9 Govt. procurement of advanced tech products (1 to 7 best) 3.8 3.5 Rule of law (-2.5 to 2.5 best) 1.9 1.2 Demography Population size (millions) 8.4 511.3 Average annual population growth (%) 0.9 0.2 Population density (inhabitants/km2) 209.7 117.5

APPENDIX III: PROFIELEN VAN BENCHMARKREGIOâ€™S, HET VLAAMS GEWEST EN BHG

Regional Innovation Scoreboard 2019 Région de Bruxelles-Capitale / Brussels Hoofdstedelijk Gewest (BE1) Norm alised Data score

Relative to BE

Tertiary education

54.4 0.720

127

Lifelong learning

12.6 0.363

152

117

International scientific co-publications

3146 1.000

136

174

Most-cited scientific publications

157

0.108 0.527

R&D expenditures public sector

0.78 0.612

102

107

R&D expenditures business sector

1.05 0.518

Non-R&D innovation expenditures

± 0.508

Product/process innovations

± 0.732

Marketing/ org. innovations

± 0.637

SMEs innovating in-house

± 0.704

Innovative SMEs collaborating

± 0.748

Public-private co-publications

88.0 0.599

105

147

PCT patent applications

2.29 0.217

Trademark applications

8.38 0.595

128

134

Design applications

1.11 0.236

Employment MHT manuf./KIS services

16.7 0.558

117

111

Sales new-to-market/firm innovations

± 0.962

Average score

-- 0.602

Brussels (BE1) is an Innovation Leader -; innovation performance has increased over time (13.5%). The table on the left shows the normalised scores per indicator and relative results compared to Belgium and the EU. The table also shows the Regional Innovation Index (RII) in 2019 compared to that of Belgium and the EU in 2019, the RII in 2019 compared to that of the EU in 2011, and performance change over time between 2011 and 2019. The radar graph shows relative strengths compared to Belgium (orange line) and the EU (blue line), showing relative strengths (e.g. Innovative SMEs collaborating) and weaknesses (e.g. Design applications). The table below shows data highlighting possible structural differences, e.g. Population density (above average) and Employment in Agriculture & Mining (below average).

BE1

EU28

Share of employment in:

Country EIS-RIS correction factor

-- 0.984

Agriculture & Mining (A-B)

0.0

1.2

4.6

Regional Innovation Index 2019

-- 0.592

Manufacturing (C)

4.9

12.7

15.4

RII 2019 (same year)

-- 105.6 121.9

Utilities & Construction (D-F)

7.5

8.4

8.2

RII 2019 (cf. to EU 2011)

Services (G-N)

72.6

68.2

64.1

Regional Innovation Index 2011

-- 0.530

Public administration (O-U)

14.8

9.4

7.0

RII 2011 (same year)

RII - change between 2011 and 2019

13.5

-- 127.7 --

98.1 114.2 --

Employment MHT man. + KIS services

4.4

5.5

58,700

35,000

30,000

GDP per capita growth (PPS), 20132017

0.83

2.19

2.86

Population density, 2017

7422

374

118

Urbanisation, 2018

100.0

88.1

76.0

Population size, 2018 (000s)

1,210

GDP per capita (PPS), 2017

± Relative-to-EU scores are not shown as these would allow recalculating confidential regional CIS data.

Sales new-to-market/firm innovations

Average employed persons per enterprise (firm size), 2015-2016

Tertiary education 200 180 160 140

11,400 512,380

Lifelong learning International scientific copublications

120 Design applications

100 80

Most-cited scientific publications

60 40 Trademark applications

R&D expenditures public sector

PCT patent applications

Public-private co-publications

Innovative SMEs collaborating SMEs innovating in-house

R&D expenditures business sector

Non-R&D innovation expenditures Product/process innovations Relative to country Marketing/organisational innovations Relative to EU

Regional Innovation Scoreboard 2019 Vlaams Gewest (BE2) Norm alised Data score

Tertiary education

Most-cited scientific publications

46.4 0.576

102

8.7 0.245

103

1862 0.769

105

134

Lifelong learning International scientific co-publications

Relative to 125

0.133 0.648

107

120

R&D expenditures public sector

0.80 0.621

104

109

R&D expenditures business sector

1.95 0.724

105

123

Non-R&D innovation expenditures

± 0.499

Product/process innovations

± 0.680

Marketing/ org. innovations

± 0.586

SMEs innovating in-house

± 0.627

Innovative SMEs collaborating

± 0.823

Public-private co-publications

90.4 0.607

106

149

PCT patent applications

4.58 0.443

113

104

Trademark applications

6.56 0.463

100

105

Design applications

3.15 0.413

112

Employment MHT manuf./KIS services

15.6 0.513

108

102

Sales new-to-market/firm innovations

± 0.787

Average score

-- 0.590

Vlaams Gewest (BE2) is a Strong + Innovator; innovation performance has increased over time (2.2%). The table on the left shows the normalised scores per indicator and relative results compared to Belgium and the EU. The table also shows the Regional Innovation Index (RII) in 2019 compared to that of Belgium and the EU in 2019, the RII in 2019 compared to that of the EU in 2011, and performance change over time between 2011 and 2019. The radar graph shows relative strengths compared to Belgium (orange line) and the EU (blue line), showing relative strengths (e.g. Innovative SMEs collaborating) and weaknesses (e.g. Lifelong learning). The table below shows data highlighting possible structural differences, e.g. Population density (above average) and Employment in Agriculture & Mining (below average).

BE2

Country EIS-RIS correction factor

-- 0.984

Agriculture & Mining (A-B)

Regional Innovation Index 2019

-- 0.580

Manufacturing (C)

RII 2019 (same year)

-- 103.5 119.4

Utilities & Construction (D-F)

RII 2019 (cf. to EU 2011)

Services (G-N)

Regional Innovation Index 2011

-- 0.570

RII 2011 (same year)

RII - change between 2011 and 2019

-- 125.1 --

-- 105.6 122.9 2.2

Public administration (O-U) Average employed persons per enterprise (firm size), 2015-2016 GDP per capita (PPS), 2017

± Relative-to-EU scores are not shown as these would allow recalculating confidential regional CIS data.

Tertiary education 250 200

1.2

4.6

12.7

15.4

8.4

8.2

68.2

64.1

7.4

9.4

7.0

4.4

5.5

35,000

30,000

2.52

2.19

2.86

487

374

118

93.0

88.1

76.0

GDP per capita growth (PPS), 20132017

Population size, 2018 (000s)

1.2 14.8

4.4

Urbanisation, 2018

Employment MHT man. + KIS services

EU28

35,900

Population density, 2017

Sales new-to-market/firm innovations

Share of employment in:

6,560

11,400 512,380

Lifelong learning International scientific copublications

150 Design applications

100

Most-cited scientific publications

50 Trademark applications

R&D expenditures public sector 0

PCT patent applications

Public-private co-publications

Innovative SMEs collaborating SMEs innovating in-house

R&D expenditures business sector

Non-R&D innovation expenditures Product/process innovations Relative to country Marketing/organisational Series2 Series3 innovations Relative to EU

Regional Innovation Scoreboard 2019 Région lémanique (CH01) Norm alised Data score

Relative to CH

Tertiary education

53.0 0.695

101

151

Lifelong learning

27.6 0.817

262 174

International scientific co-publications

3146 1.000

106

0.155 0.754

101

139

R&D expenditures public sector

0.93 0.676

100

118

R&D expenditures business sector

2.39 0.807

Most-cited scientific publications

100

137

Non-R&D innovation expenditures

n/a

Product/process innovations

± 0.509

Marketing/ org. innovations

± 0.527

SMEs innovating in-house

± 0.461

Innovative SMEs collaborating

± 0.176

237.1 0.983

241

PCT patent applications

8.90 0.747

118

175

Trademark applications

10.46 0.744

168

Design applications

2.98 0.401

Employment MHT manuf./KIS services

16.7 0.558

111

Public-private co-publications

Région lémanique (CH01) is an Innovation Leader +; innovation performance has decreased over time (0.4%). The table on the left shows the normalised scores per indicator and relative results compared to Switzerland and the EU. The table also shows the Regional Innovation Index (RII) in 2019 compared to that of Switzerland and the EU in 2019, the RII in 2019 compared to that of the EU in 2011, and performance change over time between 2011 and 2019. The radar graph shows relative strengths compared to Switzerland (orange line) and the EU (blue line), showing relative strengths (e.g. Lifelong learning) and weaknesses (e.g. Innovative SMEs collaborating). The table below shows data highlighting possible structural differences, e.g. Average employed persons per enterprise (above average) and Employment in Agriculture & Mining (below average).

Sales new-to-market/firm innovations

± 0.303

Average score

-- 0.635

Country EIS-RIS correction factor

-- 1.076

Agriculture & Mining (A-B)

2.4

3.2

4.6

Regional Innovation Index 2019

-- 0.683

Manufacturing (C)

8.1

12.6

15.4

RII 2019 (same year)

89.7 140.7

RII 2019 (cf. to EU 2011)

-- 147.3

Services (G-N)

Regional Innovation Index 2011

-- 0.685

Public administration (O-U)

RII 2011 (same year)

RII - change between 2011 and 2019

-0.4

91.5 147.7 --

CH01

Utilities & Construction (D-F)

EU28

7.3

7.5

8.2

74.1

69.4

64.1

5.3

4.7

7.0

Average employed persons per enterprise (firm size), 2015-2016 GDP per capita (PPS), 2017 *

± Relative-to-EU scores are not shown as these would allow recalculating confidential regional CIS data.

Share of employment in:

GDP per capita growth (PPS), 20132017 *

8.7

5.5

45,100

46,800

30,000 2.86

2.90

2.30

Population density, 2017

196

212

118

Urbanisation, 2018

n/a

76.0

Population size, 2018 (000s)

1,630

8,480 512,380

* Estimates for the region

Sales new-to-market/firm innovations Employment MHT man. + KIS services

Design applications

Tertiary education 300 250 200 150

Lifelong learning International scientific copublications

Most-cited scientific publications

100 Trademark applications

R&D expenditures public sector

PCT patent applications

Public-private co-publications

Innovative SMEs collaborating SMEs innovating in-house

R&D expenditures business sector

Non-R&D innovation expenditures Product/process innovations Relative to country Marketing/organisational innovations Relative to EU

Regional Innovation Scoreboard 2019 Espace Mittelland (CH02) Norm alised Data score

Relative to CH

Tertiary education

50.3 0.646

Lifelong learning

30.8 0.914

293

International scientific co-publications

2122 0.821

143

Most-cited scientific publications

141

0.116 0.562

104

R&D expenditures public sector

0.93 0.676

100

118

R&D expenditures business sector

2.39 0.807

100

137

Non-R&D innovation expenditures

n/a

Product/process innovations

± 0.589

Marketing/ org. innovations

± 0.865

SMEs innovating in-house

± 0.586

Innovative SMEs collaborating

± 0.276

Public-private co-publications

83.4 0.583

143

PCT patent applications

5.17 0.491

115

Trademark applications

5.95 0.419

Design applications

3.42 0.432

Employment MHT manuf./KIS services

17.1 0.575

115

Espace Mittelland (CH02) is an Innovation Leader +; innovation performance has increased over time (6%). The table on the left shows the normalised scores per indicator and relative results compared to Switzerland and the EU. The table also shows the Regional Innovation Index (RII) in 2019 compared to that of Switzerland and the EU in 2019, the RII in 2019 compared to that of the EU in 2011, and performance change over time between 2011 and 2019. The radar graph shows relative strengths compared to Switzerland (orange line) and the EU (blue line), showing relative strengths (e.g. Lifelong learning) and weaknesses (e.g. Innovative SMEs collaborating). The table below shows data highlighting possible structural differences, e.g. Average employed persons per enterprise (above average) and GDP per capita growth (below average).

Sales new-to-market/firm innovations

± 0.494

Average score

-- 0.608

Country EIS-RIS correction factor

-- 1.076

Agriculture & Mining (A-B)

Regional Innovation Index 2019

-- 0.655

Manufacturing (C)

RII 2019 (same year)

86.0 134.8

RII 2019 (cf. to EU 2011)

-- 141.2

Services (G-N)

Regional Innovation Index 2011

-- 0.627

Public administration (O-U)

RII 2011 (same year)

RII - change between 2011 and 2019

6.0

83.8 135.2 --

CH02

EU28

4.2

3.2

4.6

15.2

12.6

15.4

Utilities & Construction (D-F)

7.9

7.5

8.2

64.7

69.4

64.1

6.1

4.7

7.0

Average employed persons per enterprise (firm size), 2015-2016 GDP per capita (PPS), 2017 *

± Relative-to-EU scores are not shown as these would allow recalculating confidential regional CIS data.

Share of employment in:

GDP per capita growth (PPS), 20132017 *

8.7

5.5

43,000

46,800

30,000 2.86

2.20

2.30

Population density, 2017

191

212

118

Urbanisation, 2018

n/a

76.0

Population size, 2018 (000s)

1,870

8,480 512,380

* Estimates for the region

Sales new-to-market/firm innovations Employment MHT man. + KIS services

Design applications

Tertiary education 300 250 200 150

Lifelong learning International scientific copublications

Most-cited scientific publications

100 Trademark applications

R&D expenditures public sector

PCT patent applications

Public-private co-publications

Innovative SMEs collaborating SMEs innovating in-house

R&D expenditures business sector

Non-R&D innovation expenditures Product/process innovations Relative to country Marketing/organisational Series2 Series3 innovations Relative to EU

Regional Innovation Scoreboard 2019 Nordwestschweiz (CH03) Norm alised Data score

Relative to CH

Tertiary education

48.7 0.618

Lifelong learning

31.9 0.948

102

304

International scientific co-publications

3146 1.000

106

174

Most-cited scientific publications

134

0.156 0.760

101

141

R&D expenditures public sector

0.93 0.676

100

118

R&D expenditures business sector

2.39 0.807

100

137

Non-R&D innovation expenditures

n/a

Product/process innovations

± 0.525

Marketing/ org. innovations

± 0.673

SMEs innovating in-house

± 0.518

Innovative SMEs collaborating

± 0.146

245.5 1.000

100

245

PCT patent applications

9.22 0.766

122

179

Trademark applications

9.20 0.654

148

Design applications

3.27 0.422

Employment MHT manuf./KIS services

20.3 0.705

112

141

Public-private co-publications

Nordwestschweiz (CH03) is an Innovation Leader +; innovation performance has decreased over time (9%). The table on the left shows the normalised scores per indicator and relative results compared to Switzerland and the EU. The table also shows the Regional Innovation Index (RII) in 2019 compared to that of Switzerland and the EU in 2019, the RII in 2019 compared to that of the EU in 2011, and performance change over time between 2011 and 2019. The radar graph shows relative strengths compared to Switzerland (orange line) and the EU (blue line), showing relative strengths (e.g. Lifelong learning) and weaknesses (e.g. Innovative SMEs collaborating). The table below shows data highlighting possible structural differences, e.g. Population density (above average) and Employment in Agriculture & Mining (below average).

Sales new-to-market/firm innovations

± 0.584

Average score

-- 0.675

Country EIS-RIS correction factor

-- 1.076

Agriculture & Mining (A-B)

Regional Innovation Index 2019

-- 0.727

Manufacturing (C)

RII 2019 (same year)

95.4 149.6

RII 2019 (cf. to EU 2011)

-- 156.6

Services (G-N)

Regional Innovation Index 2011

-- 0.768

Public administration (O-U)

RII 2011 (same year)

RII - change between 2011 and 2019

-- 102.6 165.6 -9.0

CH03

EU28

2.1

3.2

4.6

14.8

12.6

15.4

Utilities & Construction (D-F)

7.7

7.5

8.2

69.0

69.4

64.1

4.0

4.7

7.0

Average employed persons per enterprise (firm size), 2015-2016 GDP per capita (PPS), 2017 *

± Relative-to-EU scores are not shown as these would allow recalculating confidential regional CIS data.

Share of employment in:

GDP per capita growth (PPS), 20132017 *

8.7

5.5

49,000

46,800

30,000 2.86

2.41

2.30

Population density, 2017

593

212

118

Urbanisation, 2018

n/a

76.0

Population size, 2018 (000s)

1,150

8,480 512,380

* Estimates for the region

Sales new-to-market/firm innovations Employment MHT man. + KIS services

Tertiary education 350 300 250

Lifelong learning International scientific copublications

200 Design applications

150

Most-cited scientific publications

100 Trademark applications

R&D expenditures public sector

PCT patent applications

Public-private co-publications

Innovative SMEs collaborating SMEs innovating in-house

R&D expenditures business sector

Non-R&D innovation expenditures Product/process innovations Relative to country Marketing/organisational Series2 Series3 innovations Relative to EU

Regional Innovation Scoreboard 2019 Zürich (CH04) Norm alised Data score

Relative to CH

Tertiary education

64.6 0.903

131

Lifelong learning

33.6 1.000

108

321

International scientific co-publications

3146 1.000

106

174

Most-cited scientific publications

196

0.173 0.842

112

156

R&D expenditures public sector

0.93 0.676

100

118

R&D expenditures business sector

2.39 0.807

100

137

Non-R&D innovation expenditures

n/a

Product/process innovations

± 0.700

Marketing/ org. innovations

± 0.840

SMEs innovating in-house

± 0.636

Innovative SMEs collaborating

± 0.361

239.8 0.988

242

PCT patent applications

7.15 0.635

101

149

Trademark applications

7.42 0.526

119

Design applications

1.44 0.272

Employment MHT manuf./KIS services

21.6 0.759

121

151

Public-private co-publications

Zürich (CH04) is an Innovation Leader +; innovation performance has decreased over time (-6.5%). The table on the left shows the normalised scores per indicator and relative results compared to Switzerland and the EU. The table also shows the Regional Innovation Index (RII) in 2019 compared to that of Switzerland and the EU in 2019, the RII in 2019 compared to that of the EU in 2011, and performance change over time between 2011 and 2019. The radar graph shows relative strengths compared to Switzerland (orange line) and the EU (blue line), showing relative strengths (e.g. Lifelong learning) and weaknesses (e.g. Design applications). The table below shows data highlighting possible structural differences, e.g. Population density (above average) and Employment in Agriculture & Mining (below average).

Sales new-to-market/firm innovations

± 0.615

Average score

-- 0.722

Country EIS-RIS correction factor

-- 1.076

Agriculture & Mining (A-B)

1.7

3.2

4.6

Regional Innovation Index 2019

-- 0.778

Manufacturing (C)

8.8

12.6

15.4

RII 2019 (same year)

-- 102.1 160.1

Utilities & Construction (D-F)

RII 2019 (cf. to EU 2011)

-- 167.6

Services (G-N)

Regional Innovation Index 2011

-- 0.808

Public administration (O-U)

RII 2011 (same year)

RII - change between 2011 and 2019

-- 107.9 174.1 -6.5

CH04

EU28

5.7

7.5

8.2

77.6

69.4

64.1

3.7

4.7

7.0

Average employed persons per enterprise (firm size), 2015-2016 GDP per capita (PPS), 2017 *

± Relative-to-EU scores are not shown as these would allow recalculating confidential regional CIS data.

Share of employment in:

GDP per capita growth (PPS), 20132017 *

8.7

5.5

55,500

46,800

30,000 2.86

1.70

2.30

Population density, 2017

905

212

118

Urbanisation, 2018

n/a

76.0

Population size, 2018 (000s)

1,500

8,480 512,380

* Estimates for the region

Sales new-to-market/firm innovations Employment MHT man. + KIS services

Tertiary education 350 300 250

Lifelong learning International scientific copublications

200 Design applications

150

Most-cited scientific publications

100 Trademark applications

R&D expenditures public sector

PCT patent applications

Public-private co-publications

Innovative SMEs collaborating SMEs innovating in-house

R&D expenditures business sector

Non-R&D innovation expenditures Product/process innovations Relative to country Marketing/organisational innovations Relative to EU

Regional Innovation Scoreboard 2019 Ostschweiz (CH05) Norm alised Data score

Relative to CH

Tertiary education

41.0 0.479

104

Lifelong learning

30.2 0.896

287

700 0.472

0.137 0.664

123

R&D expenditures public sector

0.93 0.676

100

118

R&D expenditures business sector

2.39 0.807

100

137

International scientific co-publications Most-cited scientific publications

Ostschweiz (CH05) is an Innovation Leader +; innovation performance has increased over time (14.1%). The table on the left shows the normalised scores per indicator and relative results compared to Switzerland and the EU. The table also shows the Regional Innovation Index (RII) in 2019 compared to that of Switzerland and the EU in 2019, the RII in 2019 compared to that of the EU in 2011, and performance change over time between 2011 and 2019. The radar graph shows relative strengths compared to Switzerland (orange line) and the EU (blue line), showing relative strengths (e.g. Lifelong learning) and weaknesses (e.g. International scientific copublications). The table below shows data highlighting possible structural differences, e.g. Employment in Manufacturing (above average) and Employment in Public administration (below average).

Non-R&D innovation expenditures

n/a

Product/process innovations

± 0.776

Marketing/ org. innovations

± 0.843

SMEs innovating in-house

± 0.633

Innovative SMEs collaborating

± 0.501

Public-private co-publications

44.5 0.426

104

PCT patent applications

6.13 0.564

132

Trademark applications

8.72 0.619

140

17.35 1.000

182

204

Employment MHT manuf./KIS services

17.2 0.579

115

Sales new-to-market/firm innovations

± 0.913

Average score

-- 0.678

Country EIS-RIS correction factor

-- 1.076

Agriculture & Mining (A-B)

Regional Innovation Index 2019

-- 0.730

Manufacturing (C)

RII 2019 (same year)

95.8 150.2

RII 2019 (cf. to EU 2011)

-- 157.3

Services (G-N)

Regional Innovation Index 2011

-- 0.664

Public administration (O-U)

RII 2011 (same year)

RII - change between 2011 and 2019

14.1

Design applications

88.7 143.1 --

CH05

EU28

4.5

3.2

4.6

16.8

12.6

15.4

Utilities & Construction (D-F)

8.4

7.5

8.2

62.7

69.4

64.1

3.8

4.7

7.0

Average employed persons per enterprise (firm size), 2015-2016 GDP per capita (PPS), 2017 *

± Relative-to-EU scores are not shown as these would allow recalculating confidential regional CIS data.

Share of employment in:

GDP per capita growth (PPS), 20132017 *

8.7

5.5

41,500

46,800

30,000 2.86

2.25

2.30

Population density, 2017

103

212

118

Urbanisation, 2018

n/a

76.0

Population size, 2018 (000s)

1,170

8,480 512,380

* Estimates for the region

Sales new-to-market/firm innovations Employment MHT man. + KIS services

Design applications

Tertiary education 300 250 200 150

Lifelong learning International scientific copublications

Most-cited scientific publications

100 Trademark applications

R&D expenditures public sector

PCT patent applications

Public-private co-publications

Innovative SMEs collaborating SMEs innovating in-house

R&D expenditures business sector

Non-R&D innovation expenditures Product/process innovations Relative to country Marketing/organisational Series2 Series3 innovations Relative to EU

Regional Innovation Scoreboard 2019 Zentralschweiz (CH06) Norm alised Data score

Relative to CH

Tertiary education

53.3 0.700

101

152

Lifelong learning

33.4 0.993

107

318

569 0.425

0.116 0.565

105

R&D expenditures public sector

0.93 0.676

100

118

R&D expenditures business sector

2.39 0.807

100

137

International scientific co-publications Most-cited scientific publications

Non-R&D innovation expenditures

n/a

Product/process innovations

± 0.607

Marketing/ org. innovations

± 0.729

SMEs innovating in-house

± 0.511

Innovative SMEs collaborating

± 0.386

166.0 0.822

201

Public-private co-publications

Zentralschweiz (CH06) is an Innovation Leader +; innovation performance has decreased over time (3.5%). The table on the left shows the normalised scores per indicator and relative results compared to Switzerland and the EU. The table also shows the Regional Innovation Index (RII) in 2019 compared to that of Switzerland and the EU in 2019, the RII in 2019 compared to that of the EU in 2011, and performance change over time between 2011 and 2019. The radar graph shows relative strengths compared to Switzerland (orange line) and the EU (blue line), showing relative strengths (e.g. Lifelong learning) and weaknesses (e.g. International scientific copublications). The table below shows data highlighting possible structural differences, e.g. Employment in Agriculture & Mining (above average) and Employment in Public administration (below average).

PCT patent applications

6.01 0.555

130

Trademark applications

14.02 1.000

131

226

Design applications

7.34 0.643

117

131

Employment MHT manuf./KIS services

19.0 0.652

104

130

Sales new-to-market/firm innovations

± 0.474

Average score

-- 0.659

Country EIS-RIS correction factor

-- 1.076

Agriculture & Mining (A-B)

Regional Innovation Index 2019

-- 0.710

Manufacturing (C)

RII 2019 (same year)

93.2 146.1

RII 2019 (cf. to EU 2011)

-- 152.9

Services (G-N)

Regional Innovation Index 2011

-- 0.726

Public administration (O-U)

RII 2011 (same year)

RII - change between 2011 and 2019

-3.5

96.9 156.5 --

CH06

EU28

4.9

3.2

4.6

14.6

12.6

15.4

Utilities & Construction (D-F)

8.6

7.5

8.2

66.1

69.4

64.1

3.8

4.7

7.0

Average employed persons per enterprise (firm size), 2015-2016 GDP per capita (PPS), 2017 *

± Relative-to-EU scores are not shown as these would allow recalculating confidential regional CIS data.

Share of employment in:

GDP per capita growth (PPS), 20132017 *

8.7

5.5

46,200

46,800

30,000 2.86

2.51

2.30

Population density, 2017

189

212

118

Urbanisation, 2018

n/a

76.0

Population size, 2018 (000s)

810

8,480 512,380

* Estimates for the region

Sales new-to-market/firm innovations Employment MHT man. + KIS services

Tertiary education 350 300 250

Lifelong learning International scientific copublications

200 Design applications

150

Most-cited scientific publications

100 Trademark applications

R&D expenditures public sector

PCT patent applications

Public-private co-publications

Innovative SMEs collaborating SMEs innovating in-house

R&D expenditures business sector

Non-R&D innovation expenditures Product/process innovations Relative to country Marketing/organisational Series2 Series3 innovations Relative to EU

Regional Innovation Scoreboard 2019 Ticino (CH07) Norm alised Data score

Relative to CH

Tertiary education

54.6 0.724

105

157

Lifelong learning

26.2 0.775

249 122

International scientific co-publications

1549 0.702

0.099 0.479

R&D expenditures public sector

0.93 0.676

100

118

R&D expenditures business sector

2.39 0.807

Most-cited scientific publications

100

137

Non-R&D innovation expenditures

n/a

Product/process innovations

± 0.880

Marketing/ org. innovations

± 0.971

SMEs innovating in-house

± 0.975

Innovative SMEs collaborating

± 0.403

77.8 0.563

138 129

Public-private co-publications

Ticino (CH07) is an Innovation Leader +; innovation performance has increased over time (17.5%). The table on the left shows the normalised scores per indicator and relative results compared to Switzerland and the EU. The table also shows the Regional Innovation Index (RII) in 2019 compared to that of Switzerland and the EU in 2019, the RII in 2019 compared to that of the EU in 2011, and performance change over time between 2011 and 2019. The radar graph shows relative strengths compared to Switzerland (orange line) and the EU (blue line), showing relative strengths (e.g. Lifelong learning) and weaknesses (e.g. Most-cited scientific publications). The table below shows data highlighting possible structural differences, e.g. GDP per capita (above average) and Employment in Manufacturing (below average).

PCT patent applications

5.94 0.550

Trademark applications

14.02 1.000

131

226

Design applications

4.95 0.524

107

Employment MHT manuf./KIS services

15.9 0.526

105

Sales new-to-market/firm innovations

± 0.768

Average score

-- 0.708

Country EIS-RIS correction factor

-- 1.076

Agriculture & Mining (A-B)

2.1

3.2

4.6

Regional Innovation Index 2019

-- 0.762

Manufacturing (C)

7.7

12.6

15.4

RII 2019 (same year)

-- 100.0 156.8

Utilities & Construction (D-F)

RII 2019 (cf. to EU 2011)

-- 164.2

Services (G-N)

Regional Innovation Index 2011

-- 0.680

Public administration (O-U)

RII 2011 (same year)

RII - change between 2011 and 2019

17.5

90.9 146.7 --

CH07

EU28

8.4

7.5

8.2

72.6

69.4

64.1

5.9

4.7

7.0

Average employed persons per enterprise (firm size), 2015-2016 GDP per capita (PPS), 2017 *

± Relative-to-EU scores are not shown as these would allow recalculating confidential regional CIS data.

Share of employment in:

GDP per capita growth (PPS), 20132017 *

8.7

5.5

50,600

46,800

30,000 2.86

2.58

2.30

Population density, 2017

130

212

118

Urbanisation, 2018

n/a

76.0

Population size, 2018 (000s)

350

8,480 512,380

* Estimates for the region

Sales new-to-market/firm innovations Employment MHT man. + KIS services

Tertiary education 250 200

Lifelong learning International scientific copublications

150 Design applications

100

Most-cited scientific publications

50 Trademark applications

R&D expenditures public sector 0

PCT patent applications

Public-private co-publications

Innovative SMEs collaborating SMEs innovating in-house

R&D expenditures business sector

Non-R&D innovation expenditures Product/process innovations Relative to country Marketing/organisational innovations Relative to EU

Regional Innovation Scoreboard 2019 Stockholm (SE11) Norm alised Data score

Relative to SE

Tertiary education

61.9 0.855

129

Lifelong learning

31.6 0.939

104

301

International scientific co-publications

3146 1.000

118

174

Most-cited scientific publications

186

0.128 0.621

108

115

R&D expenditures public sector

0.96 0.687

120

R&D expenditures business sector

2.82 0.881

112

149

Non-R&D innovation expenditures

± 0.456

Product/process innovations

± 0.591

Marketing/ org. innovations

± 0.534

SMEs innovating in-house

± 0.594

Innovative SMEs collaborating

± 0.563

Public-private co-publications

172.3 0.838

115

205

PCT patent applications

11.88 0.914

115

214

Trademark applications

13.38 0.954

142

215

Design applications

4.23 0.482

Employment MHT manuf./KIS services

25.9 0.934

141

186

Stockholm (SE11) is an Innovation Leader +; innovation performance has increased over time (0.1%). The table on the left shows the normalised scores per indicator and relative results compared to Sweden and the EU. The table also shows the Regional Innovation Index (RII) in 2019 compared to that of Sweden and the EU in 2019, the RII in 2019 compared to that of the EU in 2011, and performance change over time between 2011 and 2019. The radar graph shows relative strengths compared to Sweden (orange line) and the EU (blue line), showing relative strengths (e.g. Lifelong learning) and weaknesses (e.g. Sales new-to-market/firm innovations). The table below shows data highlighting possible structural differences, e.g. Population density (above average) and Employment in Agriculture & Mining (below average).

Sales new-to-market/firm innovations

± 0.469

Average score

-- 0.724

Country EIS-RIS correction factor

-- 1.032

Agriculture & Mining (A-B)

0.3

2.1

4.6

Regional Innovation Index 2019

-- 0.747

Manufacturing (C)

4.3

10.3

15.4

RII 2019 (same year)

-- 113.3 153.8

Utilities & Construction (D-F)

RII 2019 (cf. to EU 2011)

-- 161.1

Services (G-N)

Regional Innovation Index 2011

-- 0.747

Public administration (O-U)

RII 2011 (same year)

RII - change between 2011 and 2019

-- 112.2 160.9 0.1

SE11

GDP per capita growth (PPS), 20132017

Population density, 2017 Urbanisation, 2018 Population size, 2018 (000s)

Sales new-to-market/firm innovations Employment MHT man. + KIS services

Tertiary education 350 300 250

EU28

6.1

7.7

8.2

81.6

72.7

64.1

7.1

6.7

7.0

Average employed persons per enterprise (firm size), 2015-2016 GDP per capita (PPS), 2017

± Relative-to-EU scores are not shown as these would allow recalculating confidential regional CIS data.

Share of employment in:

4.2

5.5

49,700

36,300

30,000

1.51

1.95

2.86

351

118

36.2

60.9

76.0

2,310

10,120 512,380

Lifelong learning International scientific copublications

200 Design applications

150

Most-cited scientific publications

100 Trademark applications

R&D expenditures public sector

PCT patent applications

Public-private co-publications

Innovative SMEs collaborating SMEs innovating in-house

R&D expenditures business sector

Non-R&D innovation expenditures Product/process innovations Relative to country Marketing/organisational innovations Relative to EU

Regional Innovation Scoreboard 2019 Sydsverige (SE22) Norm alised Data score

Relative to SE

Tertiary education

52.6 0.688

104

Lifelong learning

31.6 0.939

104

301

International scientific co-publications

2395 0.872

103

152

Most-cited scientific publications

150

Sydsverige (SE22) is an Innovation Leader +; innovation performance has decreased over time (12.3%). The table on the left shows the normalised scores per indicator and relative results compared to Sweden and the EU. The table also shows the Regional Innovation Index (RII) in 2019 compared to that of Sweden and the EU in 2019, the RII in 2019 compared to that of the EU in 2011, and performance change over time between 2011 and 2019. The radar graph shows relative strengths compared to Sweden (orange line) and the EU (blue line), showing relative strengths (e.g. Lifelong learning) and weaknesses (e.g. Sales new-to-market/firm innovations). The table below shows data highlighting possible structural differences, e.g. Employment in Services (above average) and Employment in Manufacturing (below average).

0.121 0.587

102

108

R&D expenditures public sector

1.22 0.786

112

138

R&D expenditures business sector

2.04 0.742

126

Non-R&D innovation expenditures

± 0.470

Product/process innovations

± 0.534

Marketing/ org. innovations

± 0.473

SMEs innovating in-house

± 0.507

Innovative SMEs collaborating

± 0.409

79.8 0.570

140

PCT patent applications

13.59 1.000

126

234

Trademark applications

11.61 0.826

123

187

Design applications

5.50 0.553

112

113

Employment MHT manuf./KIS services

17.8 0.603

120

Sales new-to-market/firm innovations

± 0.407

Average score

-- 0.645

Country EIS-RIS correction factor

-- 1.032

Agriculture & Mining (A-B)

2.2

2.1

4.6

Regional Innovation Index 2019

-- 0.665

Manufacturing (C)

9.6

10.3

15.4

RII 2019 (same year)

-- 100.9 137.0

Utilities & Construction (D-F)

RII 2019 (cf. to EU 2011)

-- 143.4

Services (G-N)

Regional Innovation Index 2011

-- 0.722

Public administration (O-U)

RII 2011 (same year)

RII - change between 2011 and 2019

-- -12.3

Public-private co-publications

-- 108.6 155.7 --

SE22

GDP per capita growth (PPS), 20132017

Population density, 2017 Urbanisation, 2018 Population size, 2018 (000s)

Sales new-to-market/firm innovations Employment MHT man. + KIS services

Tertiary education 350 300 250

EU28

7.5

7.7

8.2

73.4

72.7

64.1

6.6

6.7

7.0

Average employed persons per enterprise (firm size), 2015-2016 GDP per capita (PPS), 2017

± Relative-to-EU scores are not shown as these would allow recalculating confidential regional CIS data.

Share of employment in:

4.2

5.5

31,300

36,300

30,000

2.37

1.95

2.86

108

118

55.6

60.9

76.0

1,500

10,120 512,380

Lifelong learning International scientific copublications

200 Design applications

150

Most-cited scientific publications

100 Trademark applications

R&D expenditures public sector

PCT patent applications

Public-private co-publications

Innovative SMEs collaborating SMEs innovating in-house

R&D expenditures business sector

Non-R&D innovation expenditures Product/process innovations Relative to country Marketing/organisational innovations Relative to EU

Regional Innovation Scoreboard 2019 Hovedstaden (DK01) Norm alised Data score

Relative to DK

Tertiary education

62.3 0.862

139

Lifelong learning

30.6 0.908

115

291

International scientific co-publications

3146 1.000

112

174

Most-cited scientific publications

188

0.137 0.667

105

123

R&D expenditures public sector

1.47 0.869

119

152

R&D expenditures business sector

3.49 0.985

133

167

Non-R&D innovation expenditures

± 0.314

Product/process innovations

± 0.516

Marketing/ org. innovations

± 0.590

SMEs innovating in-house

± 0.695

Innovative SMEs collaborating

± 0.470

245.5 1.000

123

245

PCT patent applications

8.57 0.726

118

170

Trademark applications

12.26 0.874

121

197

Design applications

9.70 0.742

114

151

Employment MHT manuf./KIS services

18.5 0.632

131

126

Sales new-to-market/firm innovations

± 0.471

Average score

-- 0.725

Public-private co-publications

Hovedstaden (DK01) is an Innovation Leader +; innovation performance has decreased over time (6.2%). The table on the left shows the normalised scores per indicator and relative results compared to Denmark and the EU. The table also shows the Regional Innovation Index (RII) in 2019 compared to that of Denmark and the EU in 2019, the RII in 2019 compared to that of the EU in 2011, and performance change over time between 2011 and 2019. The radar graph shows relative strengths compared to Denmark (orange line) and the EU (blue line), showing relative strengths (e.g. Lifelong learning) and weaknesses (e.g. Non-R&D innovation expenditures). The table below shows data highlighting possible structural differences, e.g. Population density (above average) and Employment in Agriculture & Mining (below average).

DK01

EU28

Share of employment in:

Country EIS-RIS correction factor

-- 1.012

Agriculture & Mining (A-B)

0.5

2.6

4.6

Regional Innovation Index 2019

-- 0.733

Manufacturing (C)

7.3

11.7

15.4

RII 2019 (same year)

-- 116.6 151.0

Utilities & Construction (D-F)

RII 2019 (cf. to EU 2011)

Services (G-N)

Regional Innovation Index 2011

-- 0.762

RII 2011 (same year)

RII - change between 2011 and 2019

-- 158.1 --

-- 116.8 164.3 -6.2

Public administration (O-U) Average employed persons per enterprise (firm size), 2015-2016 GDP per capita (PPS), 2017

± Relative-to-EU scores are not shown as these would allow recalculating confidential regional CIS data.

Employment MHT man. + KIS services

Design applications

250 200 150

6.5

5.3

7.0

8.0

5.5

38,400

30,000

3.68

2.86

745

137

118

92.2

61.8

76.0

Urbanisation, 2018

Tertiary education 300

8.2 64.1

8.0

Population density, 2017

Sales new-to-market/firm innovations

7.0 72.9

49,800

GDP per capita growth (PPS), 20132017

Population size, 2018 (000s)

5.1 80.1

1,820

5,780 512,380

Lifelong learning International scientific copublications

Most-cited scientific publications

100 Trademark applications

R&D expenditures public sector

PCT patent applications

Public-private co-publications

Innovative SMEs collaborating SMEs innovating in-house

R&D expenditures business sector

Non-R&D innovation expenditures Product/process innovations Relative to country Marketing/organisational innovations Relative to EU

Regional Innovation Scoreboard 2019 Helsinki-Uusimaa (FI1B) Norm alised Data score

Relative to FI

Tertiary education

52.5 0.686

126

Lifelong learning

30.4 0.902

111

289

International scientific co-publications

2850 0.952

123

166

Most-cited scientific publications

149

Helsinki-Uusimaa (FI1B) is an Innovation Leader +; innovation performance has increased over time (12.8%). The table on the left shows the normalised scores per indicator and relative results compared to Finland and the EU. The table also shows the Regional Innovation Index (RII) in 2019 compared to that of Finland and the EU in 2019, the RII in 2019 compared to that of the EU in 2011, and performance change over time between 2011 and 2019. The radar graph shows relative strengths compared to Finland (orange line) and the EU (blue line), showing relative strengths (e.g. Lifelong learning) and weaknesses (e.g. Non-R&D innovation expenditures). The table below shows data highlighting possible structural differences, e.g. Population density (above average) and Employment in Agriculture & Mining (below average).

0.111 0.541

105

100

R&D expenditures public sector

1.11 0.745

112

131

R&D expenditures business sector

2.34 0.799

115

135

Non-R&D innovation expenditures

± 0.476

Product/process innovations

± 0.794

Marketing/ org. innovations

± 0.578

SMEs innovating in-house

± 0.772

Innovative SMEs collaborating

± 0.805

Public-private co-publications

145.8 0.771

131

189

PCT patent applications

11.19 0.877

123

205

Trademark applications

13.97 0.996

155

225

Design applications

5.43 0.549

114

112

Employment MHT manuf./KIS services

22.8 0.808

143

161

Sales new-to-market/firm innovations

± 0.628

Average score

-- 0.746

Country EIS-RIS correction factor

-- 1.017

Agriculture & Mining (A-B)

0.8

4.2

4.6

Regional Innovation Index 2019

-- 0.758

Manufacturing (C)

8.9

13.4

15.4

RII 2019 (same year)

-- 116.4 156.0

Utilities & Construction (D-F)

RII 2019 (cf. to EU 2011)

-- 163.4

Services (G-N)

Regional Innovation Index 2011

-- 0.699

Public administration (O-U)

RII 2011 (same year)

RII - change between 2011 and 2019

-- 114.4 150.6 12.8

FI1B

GDP per capita growth (PPS), 20132017 Population density, 2017 Urbanisation, 2018 Population size, 2018 (000s)

Sales new-to-market/firm innovations Employment MHT man. + KIS services

Design applications

Tertiary education 300 250 200 150

EU28

7.6

8.4

8.2

77.2

69.2

64.1

5.0

4.5

7.0

Average employed persons per enterprise (firm size), 2015-2016 GDP per capita (PPS), 2017

± Relative-to-EU scores are not shown as these would allow recalculating confidential regional CIS data.

Share of employment in:

7.1

4.9

5.5

42,400

32,700

30,000

1.47

1.92

2.86

181

118

89.2

71.3

76.0

1,660

5,510 512,380

Lifelong learning International scientific copublications

Most-cited scientific publications

100 Trademark applications

R&D expenditures public sector

PCT patent applications

Public-private co-publications

Innovative SMEs collaborating SMEs innovating in-house

R&D expenditures business sector

Non-R&D innovation expenditures Product/process innovations Relative to country Marketing/organisational innovations Relative to EU

Regional Innovation Scoreboard 2019 Utrecht (NL31) Norm alised Data score

Relative to NL

Tertiary education

60.1 0.822

136

Lifelong learning

21.8 0.642

115

206

International scientific co-publications

3146 1.000

125

174

Most-cited scientific publications

179

Utrecht (NL31) is an Innovation Leader +; innovation performance has increased over time (14.3%). The table on the left shows the normalised scores per indicator and relative results compared to the Netherlands and the EU. The table also shows the Regional Innovation Index (RII) in 2019 compared to that of the Netherlands and the EU in 2019, the RII in 2019 compared to that of the EU in 2011, and performance change over time between 2011 and 2019. The radar graph shows relative strengths compared to the Netherlands (orange line) and the EU (blue line), showing relative strengths (e.g. Public-private copublications) and weaknesses (e.g. R&D expenditures business sector). The table below shows data highlighting possible structural differences, e.g. Population density (above average) and Employment in Agriculture & Mining (below average).

0.153 0.744

105

138

R&D expenditures public sector

1.37 0.838

131

147

R&D expenditures business sector

0.55 0.363

Non-R&D innovation expenditures

± 0.409

Product/process innovations

± 0.595

Marketing/ org. innovations

± 0.410

SMEs innovating in-house

± 0.437

Innovative SMEs collaborating

± 0.523

219.8 0.946

149

232

PCT patent applications

3.92 0.386

Trademark applications

7.30 0.517

117

Design applications

4.33 0.488

100

Employment MHT manuf./KIS services

17.9 0.607

121

Sales new-to-market/firm innovations

± 0.671

Average score

-- 0.631

Country EIS-RIS correction factor

-- 1.038

Regional Innovation Index 2019

-- 0.655

RII 2019 (same year)

-- 108.7 134.8

Utilities & Construction (D-F)

RII 2019 (cf. to EU 2011)

Services (G-N)

Regional Innovation Index 2011

-- 0.589

RII 2011 (same year)

RII - change between 2011 and 2019

Public-private co-publications

-- 141.2 --

-- 106.8 126.9 14.3

NL31

Agriculture & Mining (A-B)

0.9

2.2

4.6

Manufacturing (C)

5.5

9.4

15.4

Public administration (O-U) Average employed persons per enterprise (firm size), 2015-2016 GDP per capita (PPS), 2017

± Relative-to-EU scores are not shown as these would allow recalculating confidential regional CIS data.

Employment MHT man. + KIS services

200

8.2 64.1

5.9

5.8

7.0

5.1

5.5

38,400

30,000

0.43

0.79

2.86

918

501

118

99.0

90.4

76.0

Urbanisation, 2018

Tertiary education 250

5.5 68.5

5.1

GDP per capita growth (PPS), 20132017

Population size, 2018 (000s)

4.5 73.5

46,600

Population density, 2017

Sales new-to-market/firm innovations

EU28

Share of employment in:

1,300

17,180 512,380

Lifelong learning International scientific copublications

150 Design applications

100

Most-cited scientific publications

50 Trademark applications

R&D expenditures public sector 0

PCT patent applications

Public-private co-publications

Innovative SMEs collaborating SMEs innovating in-house

R&D expenditures business sector

Non-R&D innovation expenditures Product/process innovations Relative to country Marketing/organisational innovations Relative to EU

Regional Innovation Scoreboard 2019 Noord-Brabant (NL41) Norm alised Data score

Relative to NL

Tertiary education

45.5 0.560

122

Lifelong learning

17.9 0.524

168

832 0.514

0.132 0.642

119

International scientific co-publications Most-cited scientific publications

Noord-Brabant (NL41) is an Innovation Leader +; innovation performance has increased over time (6.4%). The table on the left shows the normalised scores per indicator and relative results compared to the Netherlands and the EU. The table also shows the Regional Innovation Index (RII) in 2019 compared to that of the Netherlands and the EU in 2019, the RII in 2019 compared to that of the EU in 2011, and performance change over time between 2011 and 2019. The radar graph shows relative strengths compared to the Netherlands (orange line) and the EU (blue line), showing relative strengths (e.g. PCT patent applications) and weaknesses (e.g. Marketing/organisational innovations). The table below shows data highlighting possible structural differences, e.g. Population density (above average) and Employment in Public administration

R&D expenditures public sector

0.42 0.428

R&D expenditures business sector

2.71 0.862

157

146

Non-R&D innovation expenditures

± 0.365

Product/process innovations

± 0.509

Marketing/ org. innovations

± 0.343

SMEs innovating in-house

± 0.437

Innovative SMEs collaborating

± 0.472

Public-private co-publications

149.4 0.780

123

191

PCT patent applications

13.59 1.000

169

234

Trademark applications

8.92 0.633

120

143

Design applications

9.05 0.716

146

Employment MHT manuf./KIS services

16.3 0.542

108

Sales new-to-market/firm innovations

± 0.603

Average score

-- 0.604

Country EIS-RIS correction factor

-- 1.038

Agriculture & Mining (A-B)

Regional Innovation Index 2019

-- 0.627

Manufacturing (C)

RII 2019 (same year)

-- 104.0 129.1

Utilities & Construction (D-F)

RII 2019 (cf. to EU 2011)

Services (G-N)

Regional Innovation Index 2011

-- 0.597

RII 2011 (same year)

RII - change between 2011 and 2019

-- 135.2 --

-- 108.3 128.7 6.4

2.4

2.2

4.6

13.3

9.4

15.4

Public administration (O-U) Average employed persons per enterprise (firm size), 2015-2016 GDP per capita (PPS), 2017

± Relative-to-EU scores are not shown as these would allow recalculating confidential regional CIS data.

NL41

Employment MHT man. + KIS services

200

8.2 64.1

4.6

5.8

7.0

5.1

5.5

38,400

30,000

1.31

0.79

2.86

508

501

118

91.7

90.4

76.0

Urbanisation, 2018

Tertiary education 250

5.5 68.5

5.1

GDP per capita growth (PPS), 20132017

Population size, 2018 (000s)

6.2 65.6

38,800

Population density, 2017

Sales new-to-market/firm innovations

EU28

Share of employment in:

2,530

17,180 512,380

Lifelong learning International scientific copublications

150 Design applications

100

Most-cited scientific publications

50 Trademark applications

R&D expenditures public sector 0

PCT patent applications

Public-private co-publications

Innovative SMEs collaborating SMEs innovating in-house

R&D expenditures business sector

Non-R&D innovation expenditures Product/process innovations Relative to country Marketing/organisational Series2 Series3 innovations Relative to EU

Regional Innovation Scoreboard 2019 Stuttgart (DE11) Norm alised Data score

Tertiary education

Relative to DE

39.2 0.447

126

Lifelong learning

9.4 0.266

113

International scientific co-publications

476 0.389

0.118 0.575

104

106

Most-cited scientific publications R&D expenditures public sector

0.47 0.458

R&D expenditures business sector

3.59 1.000

136

169

Non-R&D innovation expenditures

± 0.599

Product/process innovations

± 0.640

Marketing/ org. innovations

± 0.618

SMEs innovating in-house

± 0.653

Innovative SMEs collaborating

± 0.230

56.6 0.480

118

PCT patent applications

11.75 0.907

149

212

Trademark applications

7.00 0.495

112

Public-private co-publications

Design applications Employment MHT manuf./KIS services

12.92 0.860

138

176

27.5 1.000

163

199

Sales new-to-market/firm innovations

± 0.565

Average score

-- 0.599

Stuttgart (DE11) is an Innovation Leader +; innovation performance has decreased over time (-7.5%). The table on the left shows the normalised scores per indicator and relative results compared to Germany and the EU. The table also shows the Regional Innovation Index (RII) in 2019 compared to that of Germany and the EU in 2019, the RII in 2019 compared to that of the EU in 2011, and performance change over time between 2011 and 2019. The radar graph shows relative strengths compared to Germany (orange line) and the EU (blue line), showing relative strengths (e.g. PCT patent applications) and weaknesses (e.g. Innovative SMEs collaborating). The table below shows data highlighting possible structural differences, e.g. Population density (above average) and Employment in Agriculture & Mining (below average).

DE11

Country EIS-RIS correction factor

-- 1.050

Agriculture & Mining (A-B)

Regional Innovation Index 2019

-- 0.629

Manufacturing (C)

RII 2019 (same year)

-- 111.1 129.5

Utilities & Construction (D-F)

RII 2019 (cf. to EU 2011)

Services (G-N)

Regional Innovation Index 2011

-- 0.664

RII 2011 (same year) RII - change between 2011 and 2019

---

-- 135.6 --

-- 112.0 143.1 -7.5 ---

Public administration (O-U) Average employed persons per enterprise (firm size), 2015-2016 GDP per capita (PPS), 2017

± Relative-to-EU scores are not shown as these would allow recalculating confidential regional CIS data.

Tertiary education 250 200

1.5

4.6

19.3

15.4

7.1

8.2

57.3

64.1

5.5

7.0

10.1

5.5

37,100

30,000

2.92

2.82

2.86

390

234

118

87.7

79.3

76.0

GDP per capita growth (PPS), 20132017

Population size, 2018 (000s)

1.0 29.1

10.1

Urbanisation, 2018

Employment MHT man. + KIS services

EU28

47,800

Population density, 2017

Sales new-to-market/firm innovations

Share of employment in:

4,130

82,790 512,380

Lifelong learning International scientific copublications

150 Design applications

100

Most-cited scientific publications

50 Trademark applications

R&D expenditures public sector 0

PCT patent applications

Public-private co-publications

Innovative SMEs collaborating SMEs innovating in-house

R&D expenditures business sector

Non-R&D innovation expenditures Product/process innovations Relative to country Marketing/organisational innovations Relative to EU

Regional Innovation Scoreboard 2019 Karlsruhe (DE12) Norm alised Data score

Tertiary education

Most-cited scientific publications

39.3 0.449

127

9.6 0.272

115

2440 0.881

148

154

Lifelong learning International scientific co-publications

Relative to 98

0.128 0.624

112

115

R&D expenditures public sector

1.59 0.907

134

159

R&D expenditures business sector

2.92 0.897

122

152

Non-R&D innovation expenditures

± 0.641

Product/process innovations

± 0.672

Marketing/ org. innovations

± 0.671

SMEs innovating in-house

± 0.657

Innovative SMEs collaborating

± 0.326

Public-private co-publications

94.4 0.620

123

152

PCT patent applications

9.17 0.763

125

179

Trademark applications

7.77 0.551

109

124

Design applications

4.45 0.496

101

Employment MHT manuf./KIS services

22.7 0.804

131

160

Sales new-to-market/firm innovations

± 0.531

Average score

-- 0.633

Karlsruhe (DE12) is an Innovation Leader +; innovation performance has decreased over time (-8.9%). The table on the left shows the normalised scores per indicator and relative results compared to Germany and the EU. The table also shows the Regional Innovation Index (RII) in 2019 compared to that of Germany and the EU in 2019, the RII in 2019 compared to that of the EU in 2011, and performance change over time between 2011 and 2019. The radar graph shows relative strengths compared to Germany (orange line) and the EU (blue line), showing relative strengths (e.g. PCT patent applications) and weaknesses (e.g. Innovative SMEs collaborating). The table below shows data highlighting possible structural differences, e.g. Population density (above average) and Employment in Agriculture & Mining (below average).

DE12

Country EIS-RIS correction factor

-- 1.050

Agriculture & Mining (A-B)

Regional Innovation Index 2019

-- 0.665

Manufacturing (C)

RII 2019 (same year)

-- 117.4 136.9

Utilities & Construction (D-F)

RII 2019 (cf. to EU 2011)

Services (G-N)

Regional Innovation Index 2011

-- 0.706

RII 2011 (same year)

RII - change between 2011 and 2019

-- 143.3 --

-- 119.1 152.3 -8.9

Public administration (O-U) Average employed persons per enterprise (firm size), 2015-2016 GDP per capita (PPS), 2017

± Relative-to-EU scores are not shown as these would allow recalculating confidential regional CIS data.

Employment MHT man. + KIS services

Tertiary education 180 140 120

1.5

4.6

19.3

15.4

7.0

8.2

61.9

64.1

6.1

7.0

10.1

5.5

37,100

30,000

2.34

2.82

2.86

406

234

118

86.0

79.3

76.0

Urbanisation, 2018 Population size, 2018 (000s)

0.5 24.5

10.1

GDP per capita growth (PPS), 20132017

160

EU28

40,800

Population density, 2017

Sales new-to-market/firm innovations

Share of employment in:

2,800

82,790 512,380

Lifelong learning International scientific copublications

100 Design applications

Most-cited scientific publications

60 40 Trademark applications

R&D expenditures public sector

PCT patent applications

Public-private co-publications

Innovative SMEs collaborating SMEs innovating in-house

R&D expenditures business sector

Non-R&D innovation expenditures Product/process innovations Relative to country Marketing/organisational Series2 Series3 innovations Relative to EU

Regional Innovation Scoreboard 2019 Tübingen (DE14) Norm alised Data score

Tertiary education

Most-cited scientific publications

37.7 0.420

119

9.5 0.269

114

1816 0.760

128

133

Lifelong learning International scientific co-publications

Relative to 91

0.110 0.536

R&D expenditures public sector

0.96 0.688

102

120

R&D expenditures business sector

3.57 0.997

136

169

Non-R&D innovation expenditures

± 0.699

Product/process innovations

± 0.704

Marketing/ org. innovations

± 0.640

SMEs innovating in-house

± 0.726

Innovative SMEs collaborating

± 0.197

Public-private co-publications

71.9 0.541

107

133

PCT patent applications

8.99 0.752

123

176

Trademark applications

7.47 0.529

105

119

Design applications

5.26 0.540

110

Employment MHT manuf./KIS services

23.4 0.832

136

166

Sales new-to-market/firm innovations

± 0.614

Average score

-- 0.614

Tübingen (DE14) is an Innovation Leader +; innovation performance has decreased over time (-9.2%). The table on the left shows the normalised scores per indicator and relative results compared to Germany and the EU. The table also shows the Regional Innovation Index (RII) in 2019 compared to that of Germany and the EU in 2019, the RII in 2019 compared to that of the EU in 2011, and performance change over time between 2011 and 2019. The radar graph shows relative strengths compared to Germany (orange line) and the EU (blue line), showing relative strengths (e.g. PCT patent applications) and weaknesses (e.g. Innovative SMEs collaborating). The table below shows data highlighting possible structural differences, e.g. Employment in Manufacturing (above average) and Employment in Public administration (below average).

DE14

Country EIS-RIS correction factor

-- 1.050

Agriculture & Mining (A-B)

Regional Innovation Index 2019

-- 0.645

Manufacturing (C)

RII 2019 (same year)

-- 114.0 132.9

Utilities & Construction (D-F)

RII 2019 (cf. to EU 2011)

Services (G-N)

Regional Innovation Index 2011

-- 0.688

RII 2011 (same year)

RII - change between 2011 and 2019

-- 139.1 --

-- 116.0 148.3 -9.2

Public administration (O-U) Average employed persons per enterprise (firm size), 2015-2016 GDP per capita (PPS), 2017

± Relative-to-EU scores are not shown as these would allow recalculating confidential regional CIS data.

Employment MHT man. + KIS services

Tertiary education 180 140 120

1.5

4.6

19.3

15.4

7.6

8.2

55.0

64.1

5.8

7.0

10.1

5.5

37,100

30,000

3.00

2.82

2.86

212

234

118

69.7

79.3

76.0

Urbanisation, 2018 Population size, 2018 (000s)

1.8 29.8

10.1

GDP per capita growth (PPS), 20132017

160

EU28

40,400

Population density, 2017

Sales new-to-market/firm innovations

Share of employment in:

1,850

82,790 512,380

Lifelong learning International scientific copublications

100 Design applications

Most-cited scientific publications

60 40 Trademark applications

R&D expenditures public sector

PCT patent applications

Public-private co-publications

Innovative SMEs collaborating SMEs innovating in-house

R&D expenditures business sector

Non-R&D innovation expenditures Product/process innovations Relative to country Marketing/organisational innovations Relative to EU

Regional Innovation Scoreboard 2019 Oberbayern (DE21) Norm alised Data score

Tertiary education

Most-cited scientific publications

48.3 0.610

173

8.5 0.239

101

1973 0.792

133

138

Lifelong learning International scientific co-publications

Relative to 133

0.135 0.657

118

121

R&D expenditures public sector

1.06 0.726

108

127

R&D expenditures business sector

3.31 0.959

131

162

Non-R&D innovation expenditures

± 0.455

Product/process innovations

± 0.561

Marketing/ org. innovations

± 0.622

SMEs innovating in-house

± 0.572

Innovative SMEs collaborating

± 0.258

Public-private co-publications

153.5 0.791

157

194

PCT patent applications

10.17 0.821

135

192

Trademark applications

10.83 0.771

152

174

Design applications

10.45 0.771

124

157

25.1 0.902

147

180

Employment MHT manuf./KIS services Sales new-to-market/firm innovations

± 0.535

Average score

-- 0.649

Oberbayern (DE21) is an Innovation Leader +; innovation performance has decreased over time (6.5%). The table on the left shows the normalised scores per indicator and relative results compared to Germany and the EU. The table also shows the Regional Innovation Index (RII) in 2019 compared to that of Germany and the EU in 2019, the RII in 2019 compared to that of the EU in 2011, and performance change over time between 2011 and 2019. The radar graph shows relative strengths compared to Germany (orange line) and the EU (blue line), showing relative strengths (e.g. Public-private co-publications) and weaknesses (e.g. Innovative SMEs collaborating). The table below shows data highlighting possible structural differences, e.g. Population density (above average) and Employment in Utilities & Construction (below average).

DE21

Country EIS-RIS correction factor

-- 1.050

Agriculture & Mining (A-B)

Regional Innovation Index 2019

-- 0.682

Manufacturing (C)

RII 2019 (same year)

-- 120.4 140.4

Utilities & Construction (D-F)

RII 2019 (cf. to EU 2011)

Services (G-N)

Regional Innovation Index 2011

-- 0.713

RII 2011 (same year)

RII - change between 2011 and 2019

-- 147.1 --

-- 120.2 153.6 -6.5

Public administration (O-U) Average employed persons per enterprise (firm size), 2015-2016 GDP per capita (PPS), 2017

± Relative-to-EU scores are not shown as these would allow recalculating confidential regional CIS data.

Employment MHT man. + KIS services

Tertiary education 200 160 140

1.5

4.6

19.3

15.4

6.7

8.2

66.5

64.1

6.1

7.0

10.1

5.5

37,100

30,000

2.72

2.82

2.86

270

234

118

79.1

79.3

76.0

Urbanisation, 2018 Population size, 2018 (000s)

1.6 19.0

10.1

GDP per capita growth (PPS), 20132017

180

EU28

53,000

Population density, 2017

Sales new-to-market/firm innovations

Share of employment in:

4,650

82,790 512,380

Lifelong learning International scientific copublications

120 Design applications

100 80

Most-cited scientific publications

60 40 Trademark applications

R&D expenditures public sector

PCT patent applications

Public-private co-publications

Innovative SMEs collaborating SMEs innovating in-house

R&D expenditures business sector

Non-R&D innovation expenditures Product/process innovations Relative to country Marketing/organisational Series2 Series3 innovations Relative to EU

Het advies en de analyse ter ondersteuning ervan werden voorbereid door de VARIO-staf: Elie Ratinckx, Kristien Vercoutere, Annelies Wastyn, Veerle Linseele & Danielle Raspoet. VARIO wenst prof Stijn Kelchtermans (KU Leuven) te danken voor waardevolle suggesties.

Vlaamse Adviesraad voor Innoveren en Ondernemen Koolstraat 35 1000 Brussel +32 (0)2 553 24 40 info@vario.be www.vario.be