kit knowledge, innovation and territory espon 2013 programme internal seminar crossing knowledge...

KITKnowledge, Innovation and Territory

ESPON 2013 Programme Internal SeminarCrossing Knowledge Frontiers -

Serving the Territories

17-18 November 2010Liege, Belgium

The project team

Lead Partner (LP): BEST, Politecnico di Milano, Italy:Project Coordinator: Prof. Roberta Capello (Full Professor in Regional

Economics)Project Manager: Camilla Lenzi (Assistant Professor)Prof. Roberto Camagni (Full Professor in Urban Economics) Ugo Fratesi (Assistant Professor), and Andrea Caragliu (Post-Doc Fellow)

Project Partner 2 (PP2): CRENOs, University of Cagliari, Italy:Prof. Raffaele Paci (Full Professor of Applied Economics)Francesco Pigliaru (Full Professor of Economics) and Stefano Usai

(Associate Professor of Economics) Alessandra Colombelli (Post-Doc Fellow)Matteo Bellinzas (Research assistant)

Project Partner 3 (PP3): AQR, University of Barcelona, Spain:Prof. Rosina Moreno (Full Professor in Applied Economics)Prof. Jordi Suriñach (Full Professor in Applied Economics)Prof. Raúl Ramos (Associate Professor in Applied Economics)Ernest Miguélez (Technical Researcher and PhD student)

The project team

Project Partner 4 (PP4): LSE, Great Britain:Dr. Riccardo Crescenzi (Lecturer in Economic Geography) Prof. Andrés Rodríguez-Pose (Professor in Economic Geography)Prof. Michael Storper (Professor in Economic Geography)

Project Partner 5 (PP5): University of Bratislava, Slovakia:Prof. Milan Buček (Full Professor in Regional Economics and Policy)Dr. Miroslav Šipikal (Coordinator - Senior Lecturer)Dr. Rudolf Pástor (Researcher)

Project Partner 6 (PP6): University of Cardiff, Great Britain:Prof. Phil Cooke (Full Research Professor in Regional Economic

Development)Julie Porter (Coordinator – Senior Researcher/Lecturer)Selyf Morgan (Researcher)

General Goal (1)

To contribute to the understanding of:

- diffusion processes of knowledge and innovation and

- the socio-economic impacts of innovation and knowledge in space,

by identifying the different “territorial patterns of innovation” in Europe.

A territorial pattern of innovation is defined as a combination of context conditions and of specific modes of performing the different phases of the innovation process.

General Goal (2)

The general phylosophy of the project is in line with the words of Danuta Hübner (2009):

“Innovation is not considered as a linear process that starts with research, eventually leading to development, translated later into growth in the territories that have more capabilities. Instead, it is the product of a policy mix, including several bodies and stakeholders in which the territories, their specificities and conditions are paramount”.

General Goal (3)

In our project:

-> we do not look for the territorial capabilities that allow territories (in general) to exploit innovation and knowledge;

-> instead, we look for territorial specificities (context conditions) that are behind different modes of performing the different phases of the innovation process through the identification of territorial patterns of innovation.

Requirements

Requirements for achieving this goal:

- a consistent database for the state of the art in innovation and knowledge;

- comparison with the EU and national data;- identification of the most important inter-regional

spillover mechanisms;- the identification of new development opportunities

through innovation for Europe and its territories;- an inventive framework for a scientific answer to the

policy questions.

Structure of the project

B) Territorial elements explaining spatial trends.

Different modes of innovation and knowledge creation and diffusion.

A comparison with other regional knowledge economies in more advanced and emerging countries

Output: typologies of territorial patterns of innovation

WP 2 3.1 and 2.5

A) Main spatial trends of innovation and knowledge.

(both endogenous knowledge creation and flows from outside)

Output: typologies of innovative regions

WP 2.1 and 2.2

C) Impact of the different modes of innovation and knowledge on regional performance.

Output: typologies of regional performance based on innovation and knowledge

WP 2.3.2

D) Case studies

WP 2.4.1 and 2.4.2

E) Policy implications for the development of a successful knowledge economy

WP 2.6

A) Knowledge Economy and its Spatial Trends (I)

Basic idea: knowledge-based economy has not got a unique interpretative paradigm.

Different approaches are necessary:

A1. Sectoral approach (presence in the region of science-based, high-technology sectors).

A2. Functional approach (presence in the region of functions like R&D and high education).

A3. Relation-based approach (presence in the region of interactive and collective learning processes).

A) Knowledge Economy and its Spatial Trends (II)

Spatial elements matter:

- high-technology firms cluster along valleys, corridors, glens and high-tech districts to exploit the innovative atmosphere (technologically advanced regions);

- high-education and research functions cluster in space since physical proximity acts as a driver of knowledge (scientific regions);

- geographical areas characterised by cognitive proximity (shared behavioural codes, common culture, mutual trust and sense of belonging) show wider collective learning processes (networking regions).

A1) The sectoral approach: a typology

EU averageSpecialisation in HT services

Specialisation in HT manufacturing

Technologically Advanced

Regions (TAR)

HT services

HT manufacturing

Low tech regions

A1) The sectoral approachIndicators to be collected and computed:

1. Regional specialization in HT manufacturing

• As measured by employment in HT manufacturing according to Eurostat definition

2. Regional specialization in HT services

• As measured by employment in knowledge intensive HT services according to Eurostat definition

Source: Eurostat

A1) The sectoral approachHigh-tech manufacturing High-tech services

!

!

!

!

!

!!

!!

!

!

!

!

!

! !

!

!

!

!

!

!

!

!

!

!

!

!

!

!

!

!

!

!

!

!

!

!

!

!

!

!

!

!

Roma

Riga

Oslo

Bern

Wien

Kyiv

Vaduz

Paris

Praha

Minsk

Tounis

Lisboa

Skopje

Zagreb

Ankara

Madrid

Tirana

Sofiya

London Berlin

Dublin

Athinai

Tallinn

Nicosia

Beograd

Vilnius

Ar Ribat

Kishinev

Sarajevo

Helsinki

Budapest

Warszawa

Podgorica

El-Jazair

Ljubljana

Stockholm

Reykjavik

København

Bucuresti

Amsterdam

Bratislava

Luxembourg

Bruxelles/Brussel

Valletta

Acores

Guyane

Madeira

Réunion

Canarias

MartiniqueGuadeloupe

This map does notnecessarily reflect theopinion of the ESPONMonitoring Committee

0 500250km© Politecnico di Milano, Project KIT, 2010

Regional level: NUTS2Source: Politecnico di Milano, 2010

Origin of data: EUROSTAT, 2007© EuroGeographics Association for administrative boundariesTechnologically-advanced regions

LQ manufacturing (w.r. to the EU)NA0 - 0.500.51 - 11.01 - 2.942.95 - 5.37

!

!

!

!

!

!!

!!

!

!

!

!

!

! !

!

!

!

!

!

!

!

!

!

!

!

!

!

!

!

!

!

!

!

!

!

!

!

!

!

!

!

!

Roma

Riga

Oslo

Bern

Wien

Kyiv

Vaduz

Paris

Praha

Minsk

Tounis

Lisboa

Skopje

Zagreb

Ankara

Madrid

Tirana

Sofiya

London Berlin

Dublin

Athinai

Tallinn

Nicosia

Beograd

Vilnius

Ar Ribat

Kishinev

Sarajevo

Helsinki

Budapest

Warszawa

Podgorica

El-Jazair

Ljubljana

Stockholm

Reykjavik

København

Bucuresti

Amsterdam

Bratislava

Luxembourg

Bruxelles/Brussel

Valletta

Acores

Guyane

Madeira

Réunion

Canarias





Origin of data: EUROSTAT, 2007© EuroGeographics Association for administrative boundaries

Technologically-advanced regions

LQ services (w.r. to the EU)NA

0 - 0.50

0.51 - 1

1.01 - 1.78

1.79 - 3.14

A1) The sectoral approach: a typology

!

!

!

!

!

!!

!!

!

!

!

!

!

! !

!

!

!

!

!

!

!

!

!

!

!

!

!

!

!

!

!

!

!

!

!

!

!

!

!

!

!

!

Roma

Riga

Oslo

Bern

Wien

Kyiv

Vaduz

Paris

Praha

Minsk

Tounis

Lisboa

Skopje

Zagreb

Ankara

Madrid

Tirana

Sofiya

London Berlin

Dublin

Athinai

Tallinn

Nicosia

Beograd

Vilnius

Ar Ribat

Kishinev

Sarajevo

Helsinki

Budapest

Warszawa

Podgorica

El-Jazair

Ljubljana

Stockholm

Reykjavik

København

Bucuresti

Amsterdam

Bratislava

Luxembourg

Bruxelles/Brussel

Valletta

Acores

Guyane

Madeira

Réunion

Canarias





Origin of data: EUROSTAT, 2007© EuroGeographics Association for administrative boundaries


Location quotient w.r. to the EUNA

Low-tech regionsHigh.tech manufacturing regions

High-tech services regions


A2) The functional approach: a typology

EU averageHuman capital

Research activities

Scientific regions

Research intensive regions

Human capital intensive regions

Regions with other

specialisations than R&D

A2) The functional approachIndicators to be collected and computed:

•Research and development• Expenditures; Expenditure as share of GDP; Expenditures per capita

(1000 inhab.),• Personnel in R&D as share of total employment• Sources: Eurostat, ISTAT, Institut National de la Statistique et des

Études Économiques•Patents

• Number of patents; Patents per capita; Patents per capita percentage variation

• Source: OECD REGPAT•Human capital

• Share of population with degree (ISCED 5-6)• Source: Eurostat

• Fifth Framework Program• Participations; Funding; Funding per capita (Source: CORDIS)

A2) The functional approach: Human capital Tertiary education (% over population), 2005-2007

A2) The functional approach: R&D expenditures RD expenditure % of GDP, Average 2006-2007

A2) The functional approach: Patents per capita Number of patents per 1000 Pop, Average 2005-2006

A3) The relational approach: a typology

Intentional relationship

Spatial approach

Cooperative neighbouring

regions

Localised knowledge spillovers regions

Formal networking

regions

Informal networking

regions

Unintentional relationship

A-spatial approach

e.g. knowledge spillovers

e.g. scientific associations e.g. collaboration in research projects

e.g. collaboration in research projects among local actors

A3) The relational approachPossible indicators to be collected and computed:

• Participations in the 5°FP projects in the neighbouring regions • Average funding in the 5°FP in the neighbouring regions• Average funding (per capita over total population) in the 5°FP in

the neighbouring regions• Product+process innovations developed by other regions

discounted by distance• Number of patent citations on total patents• Number of in-migrant and out-migrant inventors on total

population• Number of co-patents on total patents

Sources: OECD - REGPAT, Cordis (Crenos elaboration)

A3) The relational approach: Knowledge spillover regions

!

! ! !

!

!

!

!

!

!

!!!

!

!

!

!

!

!

!

!

!!

!

!

!

!

!

!

!

!

!

!

!

!

!

!

!

!

!

!

!

!

!

!

!

!!

!

!

Acores

Guyane

Madeira

Réunion

Canarias


Valletta

Roma

Riga

Oslo

Bern

Wien

Kyiv

Vaduz

Paris

Praha

Minsk

Tounis

Lisboa

Skopje

Zagreb

Ankara

MadridTirana

Sofiya

London

Berlin

Dublin

Athinai

Tallinn

Nicosia

Beograd

Vilnius

Kishinev

Sarajevo

Helsinki

Budapest

Warszawa

Podgorica

El-Jazair

Stockholm

Reykjavik

København

Bucuresti

Amsterdam

Luxembourg

Bruxelles/Brussel

Regional level: NUTS 2Source: Cordis, 1998-2002

Origin of data: own calculations© EuroGeographics Association for administrative boundaries


© KIT Proyect, 20100 550275

km

Average number of participants in FP in the neighbouring regions

less than 93

93 to below 227

227 to below 385

385 to below 653

653 and more

A4) Spatial trends of innovation in Europe

Indicators to be collected and computed:

•Innovation•Technological innovation•Product innovation•Process innovation•Marketing and/or organisational innovation

•Adoption•Innovation adoption•Product innovation adoption•Process innovation adoption

Source: CIS/EUROSTAT

A) Spatial trends of innovation in Europe

!

!

!

!

!

!!

!!

!

!

!

!

!

! !

!

!

!

!

!

!

!

!

!

!

!

!

!

!

!

!

!

!

!

!

!

!

!

!

!

!

!

!

Roma

Riga

Oslo

Bern

Wien

Kyiv

Vaduz

Paris

Praha

Minsk

Tounis

Lisboa

Skopje

Zagreb

Ankara

Madrid

Tirana

Sofiya

London Berlin

Dublin

Athinai

Tallinn

Nicosia

Beograd

Vilnius

Ar Ribat

Kishinev

Sarajevo

Helsinki

Budapest

Warszawa

Podgorica

El-Jazair

Ljubljana

Stockholm

Reykjavik

København

Bucuresti

Amsterdam

Bratislava

Luxembourg

Bruxelles/Brussel

Valletta

Acores

Guyane

Madeira

Réunion

Canarias



0 500250km

Regional level: NUTS2Source: Politecnico di Milano, 2010Origin of data: CIS, 2004-2006 data

© EuroGeographics Association for administrative boundaries

CIS NUTS0

Technological innovation16.10 - 24.7524.76 - 37.0137.02 - 43.2943.30 - 52.4752.48 - 65.12

© Politecnico di Milano, Project KIT, 2010

!

!

!

!

!

!!

!!

!

!

!

!

!

! !

!

!

!

!

!

!

!

!

!

!

!

!

!

!

!

!

!

!

!

!

!

!

!

!

!

!

!

!

Roma

Riga

Oslo

Bern

Wien

Kyiv

Vaduz

Paris

Praha

Minsk

Tounis

Lisboa

Skopje

Zagreb

Ankara

Madrid

Tirana

Sofiya

London Berlin

Dublin

Athinai

Tallinn

Nicosia

Beograd

Vilnius

Ar Ribat

Kishinev

Sarajevo

Helsinki

Budapest

Warszawa

Podgorica

El-Jazair

Ljubljana

Stockholm

Reykjavik

København

Bucuresti

Amsterdam

Bratislava

Luxembourg

Bruxelles/Brussel

Valletta

Acores

Guyane

Madeira

Réunion

Canarias



0 500250km


© EuroGeographics Association for administrative boundariesCIS NUTS0

Product innovationNA0 - 3.283.29 - 8.598.60 - 15.7315.74 - 2525.01 - 37.77


Technological innovation Product innovation


!

!

!

!

!

!!

!!

!

!

!

!

!

! !

!

!

!

!

!

!

!

!

!

!

!

!

!

!

!

!

!

!

!

!

!

!

!

!

!

!

!

!

Roma

Riga

Oslo

Bern

Wien

Kyiv

Vaduz

Paris

Praha

Minsk

Tounis

Lisboa

Skopje

Zagreb

Ankara

Madrid

Tirana

Sofiya

London Berlin

Dublin

Athinai

Tallinn

Nicosia

Beograd

Vilnius

Ar Ribat

Kishinev

Sarajevo

Helsinki

Budapest

Warszawa

Podgorica

El-Jazair

Ljubljana

Stockholm

Reykjavik

København

Bucuresti

Amsterdam

Bratislava

Luxembourg

Bruxelles/Brussel

Valletta

Acores

Guyane

Madeira

Réunion

Canarias



0 500250km



Marketing and organizational innovationNA0 - 14.3814.39 - 23.0723.08 - 29.6929.70 - 36.4136.42 - 46.96


!

!

!

!

!

!!

!!

!

!

!

!

!

! !

!

!

!

!

!

!

!

!

!

!

!

!

!

!

!

!

!

!

!

!

!

!

!

!

!

!

!

!

Roma

Riga

Oslo

Bern

Wien

Kyiv

Vaduz

Paris

Praha

Minsk

Tounis

Lisboa

Skopje

Zagreb

Ankara

Madrid

Tirana

Sofiya

London Berlin

Dublin

Athinai

Tallinn

Nicosia

Beograd

Vilnius

Ar Ribat

Kishinev

Sarajevo

Helsinki

Budapest

Warszawa

Podgorica

El-Jazair

Ljubljana

Stockholm

Reykjavik

København

Bucuresti

Amsterdam

Bratislava

Luxembourg

Bruxelles/Brussel

Valletta

Acores

Guyane

Madeira

Réunion

Canarias



0 500250km



Process innovationNA0 - 6.296.30 - 10.5810.59 - 14.0614.07 - 17.0017.01 - 31.49


Process innovation Marketing and org. innovation


Facing some statistical difficulties at NUTS 2

• Official NUTS2 data available in a few countries– Product innovation only and process innovation only available

for IT and RO– Product innovation and process innovation available for CH, CZ,

DK, PL, UK (NUTS1)

• RIS data (DG Enterprise, JRC and MERIT) and Regional Innovation Potential (DG Regio) to be checked and validated further. ESPON contact points have already been involved.

A) Social innovation adoption and use

!

!

!

!

!

!!

!!

!

!

!

!

!

! !

!

!

!

!

!

!

!

!

!

!

!

!

!

!

!

!

!

!

!

!

!

!

!

!

!

!

!

!

Roma

Riga

Oslo

Bern

Wien

Kyiv

Vaduz

Paris

Praha

Minsk

Tounis

Lisboa

Skopje

Zagreb

Ankara

Madrid

Tirana

Sofiya

London Berlin

Dublin

Athinai

Tallinn

Nicosia

Beograd

Vilnius

Ar Ribat

Kishinev

Sarajevo

Helsinki

Budapest

Warszawa

Podgorica

El-Jazair

Ljubljana

Stockholm

Reykjavik

København

Bucuresti

Amsterdam

Bratislava

Luxembourg

Bruxelles/Brussel

Valletta

Acores

Guyane

Madeira

Réunion

Canarias





Origin of data: EUROSTAT ICT usage survey, 2009© EuroGeographics Association for administrative boundaries

Social dimension of innovation

Broadband penetration rateNA0 - 3435 - 5354 - 6869 - 87

broadband penetration rate

!

!

!

!

!

!!

!!

!

!

!

!

!

! !

!

!

!

!

!

!

!

!

!

!

!

!

!

!

!

!

!

!

!

!

!

!

!

!

!

!

!

!

Roma

Riga

Oslo

Bern

Wien

Kyiv

Vaduz

Paris

Praha

Minsk

Tounis

Lisboa

Skopje

Zagreb

Ankara

Madrid

Tirana

Sofiya

London Berlin

Dublin

Athinai

Tallinn

Nicosia

Beograd

Vilnius

Ar Ribat

Kishinev

Sarajevo

Helsinki

Budapest

Warszawa

Podgorica

El-Jazair

Ljubljana

Stockholm

Reykjavik

København

Bucuresti

Amsterdam

Bratislava

Luxembourg

Bruxelles/Brussel

Valletta

Acores

Guyane

Madeira

Réunion

Canarias





Origin of data: EUROSTAT ICT usage survey, 2009© EuroGeographics Association for administrative boundaries

Social dimension of innovation

Individuals who ordered goods or services over the InternetNA0 - 2425 - 4445 - 6162 - 80

on-line orders

A) Environmental innovation

!

!

!

!

!

!!

!!

!

!

!

!

!

! !

!

!

!

!

!

!

!

!

!

!

!

!

!

!

!

!

!

!

!

!

!

!

!

!

!

!

!

!

Roma

Riga

Oslo

Bern

Wien

Kyiv

Vaduz

Paris

Praha

Minsk

Tounis

Lisboa

Skopje

Zagreb

Ankara

Madrid

Tirana

Sofiya

London Berlin

Dublin

Athinai

Tallinn

Nicosia

Beograd

Vilnius

Ar Ribat

Kishinev

Sarajevo

Helsinki

Budapest

Warszawa

Podgorica

El-Jazair

Ljubljana

Stockholm

Reykjavik

København

Bucuresti

Amsterdam

Bratislava

Luxembourg

Bruxelles/Brussel

Valletta

Acores

Guyane

Madeira

Réunion

Canarias




Regional level: NUTS2Source: Politecnico di Milano and CRENOS, 2010

Origin of data: OECD REGPAT database, 2000-2006© EuroGeographics Association for administrative boundariesOECD green technologies

Patents per 1,000 populationNA0 - 0.0030.004 - 0.0080.009 - 0.0220.023 - 0.051

A5) Comparison with US, China and India•Innovation

•Patents (source: OECD - REGPAT)•R&D (sources: Standard & Poor’s Compustat for US; China Statistical Yearbook on

Science and Technology: Ministry of Science and Technology, Govt. of India)

•Social Filter•Education: bachelor’s, graduate or professional degrees•Education: college level education•Agricultural Labour Force•Unemployment Rate•Young People•Sources: US-Census data; Chinese statistical resources website, National Bureau of

Statistics of China; Ministry of Labour, Govt. of India, Central Statistical Organization (CSO), Census of India

•Structure of the local economy•Domestic migration•Population density•% regional of national GDP•Krugman index of specialisation• Sources: US-Census data; Chinese statistical resources website, National Bureau of

Statistics of China; Ministry of Labour, Govt. of India, Central Statistical Organization (CSO), Census of India

A5) Top 20 performers in US, China and India (patents on population)China India USA

1Beijing Delhi San Jose-San Francisco-

Oakland, CA

2Shanghai Haryana San Diego-Carlsbad-San

Marcos, CA

3Guangdong Chandigarh Appleton-Oshkosh-

Neenah, WI

4Tianjin Maharashtra Minneapolis-St. Paul-St.

Cloud, MN-WI

5Zhejiang

Andhra Pradesh

Boston-Worcester-Manchester, MA-NH

6Fujian Karnataka Cincinnati-Middletown-

Wilmington, OH-KY-IN

7Jiangsu Goa Rochester-Batavia-

Seneca Falls, NY

8Liaoning Gujarat Austin-Round Rock, TX

9Shandong Tamil Nadu Philadelphia-Camden-

Vineland, PA-NJ-DE-MD

10Hunan Pondicherry Albany-Schenectady-

Amsterdam, NY

China India USA

11 ChongqingHimachal Pradesh

Reno-Sparks, NV

12 HeilongjiangWest Bengal

New York-Newark-Bridgeport, NY-NJ-CT-PA

13 Sichuan Kerala Gainesville, FL

14 Shaanxi PunjabSeattle-Tacoma-Olympia, WA

15 JilinUttar Pradesh

Boise City-Nampa, ID

16 Hainan JharkhandChicago-Naperville-Michigan City, IL-IN-WI

17 Hubei RajasthanHouston-Baytown-Huntsville, TX

18 ShanxiMadhya Pradesh

Hartford-West Hartford-Willimantic, CT

19 Inner Mongolia

Jammu & Kashmir

Raleigh-Durham-Cary, NC

20 Xinjiang Orissa Santa Fe-Espanola, NM

B) Territorial patterns of innovation

A territorial pattern of innovation is a combination of context conditions and of specific modes of performing the different phases of the innovation process.

Context conditions:Internal generationExternal attraction

Different phases of the innovation process: - from information to knowledge- from knowledge to innovation- from innovation to regional performance

of knowledge and innovation

B1) A totally endogenous innovation pattern

Tacit knowledge

Codified knowledge

Collective learning

Entrepreneurship

Product and process innovation

Best practice

governance

Economic efficiency

REGION I

Education, human capital, accessibility, urban externalities

Territorialpreconditions for

knowledge creationKnowledge output

Territorialpreconditions for innovation

InnovationTerritorial

preconditions for innovation adoption

Economic efficiency

B2) An endogenous innovation pattern in a dynamic area






Economic efficiency

Tacit knowledge

Codified knowledge

Collective learning

Entrepreneurship


Best practice

governance

Economic efficiency

REGION J

Territorial accessibility Physical proximity


REGION I

Territorial preconditionsfor interregional knowledge flows and innovation diffusion

B3) An endogenous innovation pattern in a scientific network






Economic efficiency

Tacit knowledge

Codified knowledge

Collective learning

Entrepreneurship


Best practice

governance

Economic efficiency

REGION J

REGION I

Territorial receptivity


Tacit knowledge

Codified knowledge

Territorial relational capital



B4) An exogenously driven innovation pattern

Territorial creativity


Best practice

governanceEconomic efficiency

REGION J


REGION I







Economic efficiency

Tacit knowledge

Codified knowledge

B5) An imitative pattern of innovation

Territorial attractiveness


Best practice

governance

Economic efficiency

REGION J


REGION I







Economic efficiency

Tacit knowledge

Codified knowledge

Collective learning

Entrepreneurship


B6) An integrated innovation pattern






Economic efficiency

REGION J



Collective learning

Entrepreneurship


Best practice

governanceEconomic efficiency

REGION I


Tacit knowledge

Territorial relational capital

Territorial receptivity

Tacit knowledge

Codified knowledge

Codified knowledge

Territorial attractiveness

Collective learning

Entrepreneurship


Territorial creativity

C) Impact of innovation and knowledge on regional growth

This WP will identify:

- the role of innovation and knowledge on the performance of different territories;

- the return of investments in regional innovation and knowledge in different territories;

- the role of knowledge spillovers in the economic performance of different territories.

D) Case studies2 case studies per PP on regional best practices in knowledge creation

2 case studies per PP on regional best practices in knowledge spillovers

Overall 12 case studies

1. Regions selection according to two dichotomies (see the next slide):• Concentrated vs diversified• Traditional vs advanced

2. Aim of the case studies: - to strengthen the role of territorial elements in knowledge and innovation creation and knowledge spillovers according to the conceptual framework used in the project of territorial pattern of innovation- to highlight the governance elements related to knowledge and innovation diffusion

3. Knowledge spillovers among regions and not only within regions

4. Agreement on the interview protocol, target groups of the planned interviews and selection process of the interviewees (to be provided in the Interim Report)

D) Case studies

CONCENTRATED AREAS DIVERSIFIED AREAS

TRADITIONALSECTORS

Wood processing industry - Banska Bystrica region Automotive - Bratislava

Food- WalesWine – Tuscany

Automotive – Piemonte

ADVANCEDSECTORS

Biotechnology – OxfordICT – Košice

ICT – Bratislava

Digital Media/TV – Cardiff (Wales)Media – Milan (Lombardy)

ICT – CambridgeArno Valley – High tech (Tuscany)

E) Policy recommendationsThe aim of the project is to produce policy recommendations on the achievement of a “smart growth” for Europe, intended as an economic growth based on knowledge and innovation.

In “EU2020” this priority rejects a “one size fits all approach”.

Recommendations in this field have to: •be tailored on each “territorial pattern of innovation”•be based on specific policy interventions •reinforce territorial preconditions that strengthen each

innovation pattern in terms of economic performance.

kit knowledge, innovation and territory espon 2013 programme internal seminar crossing knowledge...

Documents

research professor

project team project

project coordinator

innovation process

michael storper professor

ral ramos associate

general goal

project team lead partner