Entrepreneurship and the Geography of Innovation Wolfgang POLTfapesp.br/eventos/2017/insyspo/PDF/06-07/15h_Wolfgang-Polt.pdf · Findings stress importance of customers and suppliers

SymposiumEntrepreneurship and

the Geography of

Innovation

FAPESP/Sao Paulo

July 6 2017

Photo:

5278205683_dcbcda7fea_o_Flickr_CCAttribution_BY_Horia_Varian_Modified

This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement

No 64935. The European Commission has no liability in respect for the above contents.

Wolfgang POLT

(JOANNEUM Research)

Lisa Dale-Clough, Luke Georghiou (Uni

Manchester), Katrin Hahn (Uni Delft),

Enikö Linshalm, Angelika Sauer

(Joanneum Research), Erkki Ormala

(Aalto University)

Business/Innovation Eco-Systems in

Europe – an empirical study

The Industrial Innovation in Transition (IIT) Project


No 64935. The European Commission has no liability in respect for the above contents.Photo:


The team:





“The Industrial Innovation in Transition (IIT) project aims to understand how innovation processes in European industry are changing [in the past 10 years] and to disseminate the best practices in this field between companies and government agencies.”

694 company case studies during 2015-16

11 European countries (Austria, Czech Republic, Estonia, Finland, Ireland, Italy, Germany, Netherlands, Portugal, Spain and United Kingdom)

5 sectors (Agri-Food, Bio-Pharmaceutical, Clean-Technology, ICT and Manufacturing)





Central instrument: a survey of innovative companies using in-depth interviews. Recorded, transcriptions subsequently coded for quantitative & qualitative analysis (n=694).

Survey to triangulate hypotheses from the interview analysis (n=315).

Key areas of investigation:

Business/ Innovation Ecosystem

New Tools for Innovation Management

Open Innovation

Innovation Management and Practice

Absorptive capacity of firms Further aim to assess adequacy of current policy

frameworks and instruments

Starting points – perceptions of a changing paradigm

Long term structures of post-war science and innovation built around largely self-sufficient major firms benefitting from science as a public good

From 1980s cost pressures, rapid pace of technological change in critical technologies and political pressure for science base to demonstrate its contribution to socio-economic goals shifted system to a greater focus on externalisation / outsourcing and market transactions

Policy thinking followed and key concepts of innovation systems were matched by stronger emphasis upon promoting collaboration

By early 2000s crystallizing into concepts of open innovation and innovation ecosystems

This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 64935.

The European Commission has no liability in respect for the above contents.

Key characteristics of the shift in innovation paradigms

Large multiproduct, multi-technology firms complemented by dynamic population of smaller companies sustained by venture capital.

Complex patterns of birth, growth, acquisition, or death of the firms enable effective selection of technologies.

Increased outsourcing of R&D to specialist organisations & universities.

Networks and alliances built around technologies, standards and supply chains.

Globalisation in R&D driven more by local capabilities in people and scientific institutions.

Lead markets precede adaptation to markets.

1. From Coombs R and Georghiou L, A New “Industrial Ecology” Science Vol 296 19 April 2002This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 64935.


Distinguishing innovation ecosystems

The innovation ecosystem focuses upon the dynamics of the wider environment in which innovation takes place. It encompasses both the ‘opening up’ of innovation & the focus on institutions in the innovation systems approach.

The distinction is on understanding interactions, flows and interdependencies at a systemic level:

“The added value of thinking of this system as an ecology is the focus it brings to the distribution and abundance of research performers and knowledge and their interactions with each other and the broader environment” (ERA Rationales Report, European Commission 2008: 23)



Elements of Innovation Ecosystems

Source: L.Georghiou cited in House of Commons Select Committee on Science & Technology Report Bridging the valley of

death: improving the commercialisation of Research, March 2013 Th

is p

roje

ct

has r

eceiv

ed f

undin

g f

rom

the E

uro

pean U

nio

n’s

Horizon 2

020 r

esearc

h a

nd in

novatio

n p

rogra

mm

e u

nder

gra

nt

agre

em

ent

No 6

4935.

Th

e E

uro

pean C

om

mis

sio

n h

as n

o lia

bili

ty in

respect fo

r th

e a

bove c

onte

nts

.

Percentage of firms considering ecosystem concept relevant for their innovation

activities (interviews)

83,70%

95,70%

94,80%

92,40%

98,40%

16,30%

4,30%

5,20%

7,60%

1,60%

Agri-food

Biopharma

Clean technologies

ICT

Manufacturing

Relevant Not Relevant



(Overall) Change in relevance of innovation ecosystems in the last 5-10 years




56%

44%

0%0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

Increased No change Decresed

Change in IES relevance

ALL (n=464)

Innovation ecosystem approaches:

by company size (% of answering: fully agree, from survey)


The European Commission has no liability in respect for the above contents. Photo: 5278205683_dcbcda7fea_o_Flickr_CCAttribution_BY_Horia_Varian_Modified

28%26%

23%

17%

11%

8%

21%20%

19%21%

5% 3%

21% 22%

17%

8% 8%6%

22%

29%

15%13%

1% 4%

21%

31%

21%

13%

7% 7%

0%

5%

10%

15%

20%

25%

30%

35%

...in

crea

sin

gly

enga

ged

in

asso

ciat

ion

s/b

oar

ds/

com

mit

tee

s to

exe

rt s

trat

egic

in

flu

ence

on

le

gal/

stan

dar

diz

atio

n/…

...in

cre

asin

gly

enga

ged

wit

hre

sear

ch o

rgan

isat

ion

s to

lear

n a

bo

ut

tech

no

logi

cal

op

po

rtu

nit

ies.

...in

crea

sin

gly

enga

ged

wit

h

exte

rnal

par

tner

s w

ith

d

iffe

ren

t b

ackg

rou

nd

s to

u

nd

erst

and

bet

ter

the

po

ten

tial

of

…

...r

estr

icte

d e

nga

gem

ent

to

lon

g-te

rm a

nd

tru

sted

p

artn

ers

in a

clo

se b

ilate

ral

way

in o

rder

to

pro

tect

in

tern

al…

...e

nga

ged

less

wit

h o

the

rs in

thei

r b

usi

nes

s en

viro

nm

ent.

...d

id n

ot

mak

e ch

ange

s in

thei

r co

llab

ora

tive

inn

ova

tio

nac

tivi

tie

s.

During the last five years companies ...

<10 Micro 10-49 Small 50-249 Medium-sized 250-3.000 Large >3.000 Very large

Most important elements of the innovation ecosystem (source: interviews)

0%

10%

20%

30%

40%

50%

60%

70%

80%

knowledge flows mobility of people financial support services Other

Agri-food Biopharma Clean technologies ICT Manufacturing



Innovation Ecosystemenable new ways of knowledge creation and utilization

Demand

orchestration

Innovationorchestration

Architecture

orchestration

Supply

orchestration

Demand

orchestration

Architecture

orchestration

Supply

orchestrationInnovation

orchestration

Demand

orchestration

Architecture

orchestration

Supply


orchestration

Demand

orchestration

Architecture

orchestration

Supply


orchestration

Demand

orchestration

Architecture

orchestration

Supply


orchestration

Demand

orchestration

Architecture

orchestration

Supply


orchestration

Demand

orchestration

Architecture

orchestration

Supply


orchestration

Demand

orchestration

Architecture

orchestration

Supply


orchestration

Demand

orchestration

Architecture

orchestration

Supply


orchestration

Core

Partners

with ”orchestration capability”to ”extended enterprise”

Core

From traditional

large enterprise



Ecosystem perspective on innovation policy leads to different questions

Is the population of actors ‘balanced’? Country/region has a balance between large multiproduct, multi-

technology firms who can act as system integrators and coordinate ecosystem ‘initiation’, ‘maintenance’ and ‘development’?

Is there a dynamic population of smaller companies sustained by venture capital who can provide innovative ideas and products?

What is the role for established SMEs?

How different does this ecosystem look across sectors? Are those differences driven by the nature of the technology and/or market or historic drivers?

Is there sufficient demand for innovation in the system? Are public and private procurers sufficiently capable and incentivised to

drive demand for innovation?

Are new solutions being crowded out by lock-in to existing standards, regulations and structures?



Organising policy: capturing value and levers for change

The innovation ecosystem leaders often design the roles of different actors (and their share of the value generated), coordinates interactions within the ecosystem and between ecosystems, and orchestrate resources flow between different partners as the system evolves (Adner, 2012)

Therefore, innovation ecosystem leadership affects the innovation trajectories of the all of the actors involved – underperformance or excessive dominance over value capture may require levers to change innovation ecosystem leadership.

Licensing, corporate venturing and scaling-up new firms could induce a change in dominant actors or knowledge and be the target for policy interventions.

A policymaker may apply incentives to change framework conditions such as reducing barriers to mobility.

Companies may seek to establish new ecosystems. (e.g. via OI) This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement


Role of Policy in Innovation Ecosystems

The policymaker’s role is not ‘Olympian’ overview - lack of any objective position and the essence of an ecosystem is shared governance.

Policymakers become active players, able to adjust the balance, enhance or moderate flows through certain instruments , e.g. foresight and platforms to develop IES leaders, and frameworks of instruments.

Policy adapts with ecosystem evolution? Early stages are potentially volatile, viable networks require certain conditions, resources and activities (Dedehayir et al., 2016).

Core problem: policy boundaries and innovation ecosystems Innovation ecosystems are often international and not always clearly focused on a

particular technology field, creating challenges for organising innovation policy. The value blueprint of different IES’ results from the location of, and links between,

innovation ecosystem actors, with different advantages and shortfalls over time (Adner, 2012).

Requires deployment of different instruments in different places, directed towards different actors at different times.

Best way to support a deficiency in one actor may be targeting a policy at another.



Future policy needs Emphasis on knowledge flows places focus on balance of actors & vectors of

knowledge transfer – ‘population approach’

Findings stress importance of customers and suppliers but few policy instruments explicitly aimed at supply chains

For new technologies challenge even greater to create new demand channels placing focus on procurement/lead market approaches

Demand is a common deficiency in ecosystems explaining why national and regional administrations seek to attract and retain ‘anchor firms’ but as these consolidate and become fewer in number there is a need for alternative approaches

Need tools to open up underperforming existing innovation ecosystems (governance and demand) and create new ones

Foresight needed as tool for ecosystem coordination



Next steps and continuation




Final report by End of July 2017

Final Discussion with EU Commission September 2017

Dissemination activities till December 2017

Possibility for continuation of research, bringing in more partners from other countries (to be discussed and agreed upon with EU COM)

Trial access to project DB

Future extension of country basis, cooperation with the team and access to DB

Thank you for your attention !

[email protected]

Photo:




Supplementary Slides

Photo:




31 © NOKIA EO./16.1.2008

New Tools for Innovation Management




New innovation models and tools for innovation – such as the customer driven innovation model, web enabled tools and big data – allow companies to blend the physical and virtual worlds of innovation activities and they have become important means of supporting effective innovation practices.

The physical and virtual worlds blend allowing people to contribute and be involved

Clouds, Do-It-Yourself (DIY), social media, blended worlds and sensing surroundings will become key platforms for innovation.

Creativity and imagination combined with good competence are key characteristics of future innovators.

32 © NOKIA EO./16.1.2008

Open Innovation...




...is the opening-up of innovation processes to allow

ideas, new technologies or feedback from external

partners to flow into the company, or actively seek

out and use external knowledge.

Engeging external partners:

access and drive global intellectual vision and

insight

form strategic collaborations with world-leading

institutions to multiply our efforts

build global test beds to learn from broader

audiences

33 © NOKIA EO./16.1.2008

Open Innovation/Knowledge Sharing




Complementary competence and excellence

Genuine commitment for knowledge sharing/trust

Collaboration platforms/joint campus presence

Mobility of research personnel

R&D/recruitment/education all involved

Transparent management and collaboration rules

Fair rules for IPR ownership and use

• Reformed reward and incentive systems

34 © NOKIA EO./16.1.2008

Innovation management and practice

The key question regarding the management structure of the

innovation processes within a company is whether innovation

activities take place in different business lines/units or within a

centralized R&D department. The IIT results indicate that both

principles are used by companies, and oftentimes in combination.

• State-gate model dominates

• Still most initiatives cost driven

• Top management has decisive role

• Dedicated central innovation committee

• Innovation knowledge sourced outside more important, but

often difficult to absorb

• Changes in innovation management practice still in progress

(customer involvement, business incubators, independent

innovation units, web-enabled innovation platforms, etc.)




Big Data usage in Innovation;

Industry Sectors




29% 30% 31%

46%

23%

71% 70% 69%

54%

77%

0

20

40

60

80

100

Agrofood Biopharma Cleantechnologies

ICT Manufacturing

Use of BIG DATA (ALL, n=563)

Yes NO

Open Innovation

• Access and drive global intellectual vision and insight

• Form strategic collaborations with world-leading institutions to multiply our efforts

• Build global test beds to learn from broader audiences

Engaging external partners




25%

20%18%

15%11%

7%4%

0%

5%

10%

15%

20%

25%

30%

Customers Publicresearch

Suppliers Regulators Finance Other Other infra

Innovation Ecosystem StakeholdersTotal n=694

ALL




IES interactions: OI-activities

• All, N = 566

• 76 % of the companies indicated

that they engage in OI-activities.

62%

14%

27%

0%

20%

40%

60%

80%

100%

Rely on a regular basis Started to rely on outside organizations Do not rely on outside organizations

Inno-related knowledge sourced from outside

ALL





0

10

20

30

40

50

60

Stage-gate Flexible Customer driven Other

Agro-food Bio-Pharma Clean tech ICT Manufacturing


• State-gate model dominates

• Still most initiatives cost driven

• Top management has decisive role

• Dedicated central innovation committee

• Innovation knowledge sourced outside more important, but often difficult to absorb

• Changes in innovation management practice still in progress (customer involvement, business incubators, independent innovation units, web-enabled innovation platforms, etc.)







Includes only “yes”-answers, multiple choices were allowed.

55,6% 54,5% 52,7%

42,3% 41,9% 37,1% 34,3% 34,1%

23,8%

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

ALL

Barriers to innovation

Main Factors at the start of an innovation project

17,2% 20,7% 19,0% 12,9%26,3%

57,6% 56,5%52,6% 63,6%

64,7%

29,3%35,9%

21,6%27,3%

28,6%

24,2%

50,0%

29,3%

28,8%

32,9%17,2%

14,1%

20,7%16,7%

21,2%

6,1%

5,4%

8,6%4,5%

6,3%

0,0%

20,0%

40,0%

60,0%

80,0%

100,0%

120,0%

140,0%

160,0%

180,0%

200,0%

Agri-food Biopharma Clean technologies ICT Manufacturing

employee driven cost-driven customer-driven product-driven R&D-driven other



Main decision making actors

13,3% 20,0%36,0%

12,5%

52,2%24,6% 25,0%

57,8%

8,3%24,7%

73,3%90,7%

72,0%93,8%

71,1%

59,4% 56,8%

88,9%

62,5%

68,0%

59,1%

10,7%

40,0%

3,8%

26,7%

13,0% 13,6%

35,6%

18,8%

20,0%

15,1%4,0%

12,0%

0,0%

52,2%

5,8%

57,8%

0,0%

52,0%

2,2%10,7%

4,0%

34,0%

25,0%

14,4%

50,7%

4,5%

26,7%

8,3%

8,0%

11,8%

0,0%

50,0%

100,0%

150,0%

200,0%

250,0%

300,0%

350,0%

AT CZ DE EE ES FI IE IT NL PT UK

R&D deparment General management Dedicated central innovation commitee

Development department only Research department only Strategic business units

Marketing Other



Most frequently mentioned policy gaps




Insufficiently skilled people and development of talent/capabilities

• Systemic bias/difficulties for small firms

• Regulation around innovation (seen both as barrier and positive factor)

• Need for more demonstrators, pre-commercial procurement, procurement of innovation

• Insufficient grant funding available

• Insufficient seed, venture and growth funding

• Global trade difficulties

• Difficulties in knowledge transfer from research sector

• Bureaucracy and complexity in policy support

• Lack of coordination and consistency over time in policy environment




44%

56%

42%

39%

19%

44%

30%

18%

38%

24%

32%

5%

3%

1%

2%

15%

2%

6%

13%

6%

5%

16%

3%

1%

15%

2%

22%

10%

28%

12%

16%

5%

10%

4%

15%

4%

11%

12%

5%

14%

12%

1%

15%

4%

24%

10%

5%

3%

0%

11%

7%

1%

12%

17%

3%

10%

20%

26%

6%

3%

3%

35%

13%

17%

11%

9%

23%

3%

26%

14%

7%

13%

20%

13%

14%

9%

22%

11%

0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%

AT

CZ

DE

EE

ES

FI

IE

IT

NL

PT

UK

MOST IMPORTANT PUBLIC POLICY INITIATIVES

R&D Grants R&D Loans Tax incentives Public procurement Educ& Training Cons. Support Publ. Research Other

Ecosystem Barriers Policy challenge

Policy measures

Flo

w

People Lack of capabilities or skills

Skills deficits • Training and advice in capabilities • Encourage recruitment of skills• Reduction of mobility barriers

Finance Access Insufficient access

• Grants, loans and fiscal incentives • Mobilise private finance (co-investment, risk-

sharing , facilitate venture capital

Conditions and priorities of public funding

• Simplification (processes)• Foresight on priorities/strategy• Timeliness (evolution of ecosystems) Coherence

and consistency

Knowledge Access Partnership issues

• Promotion of science-industry links• Diffusion measures

IP system • Patent box

Services Exchanges enableinnovation

Reliance on external knowledge for innovation

• Support RTOs, standards bodies, measurement and testing services, access to consultancy and professional services.

• Digitalisation and adoption of ICT within business and innovation planning and implementation.

Addressing barriers and policy deficits – a systematic overview

Ecosystem Barriers Policy challenge Policy measures

Syst

em

ic c

on

sid

era

tio

ns

Regulation and Standards

Reg’tion • Challenging frameworks (e.g. REACH) or clinical trials regulation and costs of compliance.

• Lack of stability in regulation.

• Varied compliance prevents level playing field.

• Simplification• Proactive regulation• Embed regulators in

ecosystems.

Standards • Standards projectsLow demand for innovation

Access to markets

• Market barriers in the public sector

• International trade issues

• PPI• PCP• Supply chain measures

Intermediary institutions

• [Lack of middle TRL R&D]• [Lack of technology

infrastructure]• [Lack of capacity to assist

firms]

• Support RTOs, standards bodies, measurement and testing services, consultancy support, business support agencies


Ecosystem Barriers Policy challenge / gap • Policy measures

Syst

em

ic c

on

sid

erat

ion

s

Populations of actors and entry/exit conditions

• [Deficiencies in anchor firms]

• [Lack of entrepreneurship]

• Promote technological inward investment

• Support for scale-up firms

• Support for start-ups• Student

entrepreneurship education & support

System transformation

• [Lock in]• [Coordination failure]

• Challenge-based initiatives

• New mission-oriented research


Documents

Entrepreneurship and the Geography of Innovation Wolfgang POLTfapesp.br/eventos/2017/insyspo/PDF/06-07/15h_Wolfgang-Polt.pdf · Findings stress importance of customers and suppliers