Transcript Regional innovation dynamics within emerging fields: a

The role of science - industry interactions within
emerging fields: An analysis of technological
performance on the level of regions and firms
Cathy Lecocq
Dimetic session, Pecs, July 2007
The role of science - industry interactions within emerging fields
PhD Framework:
The role of science – industry interactions for the technological performance of regions and
firms in new emerging fields
The role of (national/regional) policies aimed at stimulating the collaboration between academia
and industry, and their distinctive impact on inter-organisation collaboration at the level
of the firm and the region.
SCIENCE –
TECHNOLOGY
INTERACTIONS
1. Technological performance of
REGIONS
2. Technological performance of
FIRMS
3. POLICIES aimed at stimulating science – industry interactions
The role of science - industry interactions within
emerging fields

Using formal R&D collaborations, based on co-publication and co-patenting data
=>

hereby exploring the relevancy of this set of indicators as comprehensive measures for the
amount and nature of scientific and technological collaboration on the level of regions and firms.
Focusing in a first phase on biotechnology, which can be considered as an emergent
and growing field of technological and economical activity over the last decades
In a next step, this pilot will be extended towards other technology fields in order to
check whether and to what extent the role of science – industry interactions is really
distinctive within emerging, knowledge intensive technologies
Collaboration between Academia and Industry
and the technological Performance of European
Regions: the Case of Biotechnology
Catherine Lecocq
Bart Van Looy
Managerial Economics, Strategy and Innovation
Faculty of Economics and Applied Economics
K.U.Leuven
Science-Industry interaction
and the technological performance of regions
System approach of innovation: interaction between multiple actors
Innovation Systems



(National) Innovation Systems (Lundvall, 1992; Freeman, 1987; Nelson, 1993)
Regional dynamics (Acs, 2000; Blind and Grupp, 1999; Cooke, 2002; Florida and
Cohen, 1999; Keeble and Wilkinson, 2000; Saxenian, 1994)
Triple Helix model (Leydesdorff and Etzkowitz, 1996; 1998)
Firms
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


Suppliers and customers (Shaw, 1994; Von Hippel, 1988)
Potential lead users (Quinn, 1985; Von Hippel et al., 1999)
Universities and public research centres (Gerwin et al., 1992, Santoro, 2000; Tidd
et al., 2002, Veugelers and Cassiman, 2005)
Future or existing competitors (Hamel, 1991; Dodgson, 1993)
Open Innovation paradigm (Chesbrough, 2003)
Science-Industry interaction
and the technological performance of regions
Recent research on R&D collaboration of firms differentiates between different
types of alliances based on March’s (1991) exploration vs exploitation
framework and indicates differentiated relationships with
innovative
performance (multi-dimensional):

Integrated product development path (Rothaermel and Deeds, 2004; 2006):
exploration alliances -> products in development -> exploitation alliances -> new
products on the market

Firms engaging more in collaboration with universities and knowledge generating
institutes perform better in terms of the development of new technologies and products
(Belderbos et al., 2004; Faems et al.,2005)

Firms engaging in exploitative collaborations with other firms perform better in terms of
obtaining turnover from improved products (Faems et al., 2005) or show a significant
impact on labour productivity growth (Belderbos et al., 2004).
Science-Industry interaction
and the technological performance of regions
For knowledge creation and diffusion processes involving a substantial amount of
tacit knowledge proximity matters (Malmberg and Maskell, 1997; 1999
Jaffe, Trajtenberg, and Henderson, 1993, Anselin, Varga and Acs, 1997)

Universities and research labs contribute to the technological and innovative
performance of their regions (Jaffe, 1989; 1993; Mansfield, 1995; Acs et al. 1991;
2002; Anselin et al. 1997; Varga, 2002; Fischer et al. 2003)

But seems more pronounced within certain (broad) technological fields than across
all fields (Jaffe, 1989; Acs, et al., 1991; Anselin et al. 2000)

Results in increasing attention for regional innovation dynamics/clusters: unit of
analysis within this study
Science-Industry interaction
and the technological performance of regions
Technologies progress along a Technology Life Cycle (Utterback and Abernathy
1975; Roussel, 1984; Foster 1986; Anderson and Tushman, 1997; Andersen
2001)
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Different stages of technology coincide with different characteristics of the
technologies with respect to technical and market uncertainty, technical
performance, levels of R&D investments, etc. (Roussel, 1984; Foster 1986)

The development path of technologies typically follows an S-shaped growth path
(Andersen 2001)
Science-Industry interaction
and the technological performance of regions
We hypothesize that the nature and impact of university – industry
collaborations for regional development vary as technologies and
industries progress along the technology/product life cycle.
And more specifically :
1)
More R&D collaborations between companies and universities/ research
centres will lead to better technological performance of regions (within
emerging, knowledge intensive, fields) during the first, more explorative,
phases of the technology life cycle.
2)
More R&D collaboration between companies will lead to better technological
performance of the regions during next, more exploitation oriented phases of
the technology life cycle.
Science-Industry interaction
and the technological performance of regions
DATA:
EPO patents -> consistent, field specific and comparable data for a large number of regions
and over longer time periods
Assignee(s):
Name(s)
Addresse(s)
Patent
Technology
class (IPC code)
Inventor(s):
Name(s)
Adresses(s)
Science-Industry interaction
and the technological performance of regions
EPO patents within the domain of Biotechnology (appl years 1978-2001)
Result of a prior effort to map the field of biotechnology (Glänzel et al., 2003)

Assignment of assignee type : University, public research centre,
company, hospital, private person
Based on the sector assignment methodology developed by the Policy Research
Centre for R&D Statistics (Leuven, Belgium, see Van Looy, Du Plessis & Magerman,
Eurostat WP, 2006)

Allocation of addresses to regions: nuts 3 level
Using the 3-level hierarchical classification of regions established by Eurostat: the
Nomenclature of Territorial Units for Statistics (NUTS)

Selection of nuts level: nuts1/2
Nuts1 for smaller European countries, nuts 2 for other countries
Criterion: average population on the region level > 1 mio
Science-Industry interaction
and the technological performance of regions
Overview of selected nuts level, number of regions and average population
per country ( EU-15 + Switzerland)
Country
Austria
Belgium
Denmark
Finland
France
Germany
Greece
Ireland
Italy
Luxembourg
Netherlands
Portugal
Spain
Sweden
Switzerland
United Kingdom
Total
Nuts level
Number of regions
Nuts1
Nuts1
Nuts2
Nuts2
Nuts2
Nuts2
Nuts1
Nuts2
Nuts2
Nuts1
Nuts2
Nuts2
Nuts2
Nuts2
Nuts2
Nuts2
3
3
1
5
26
41
4
2
21
1
12
7
19
8
7
37
197
Average population
(in ‘000)
2.681
3.429
5.355
1.038
2.351
2.008
2.738
1.920
2.713
442
1.337
1.470
2.143
1.112
1.032
1.598
1.964
Science-Industry interaction
and the technological performance of regions
Indicators of technological performance of regions
(based on inventor addresses)
Number of patents
Patents per population
Patent count per region per year
Patent count per million inhabitants of the region
Collaboration indicators
(based on co-assigneeship, allocated to regions based on assignee addresses)
KGI – I collaboration
I – I collaboration
Co-patenting between at least one knowledge generating
institute (university or public research institute) and one or
more industrial partners
Co-patenting between 2 or more industrial partners
Science-Industry interaction
and the technological performance of regions
Panel dataset with 4.728 observations pertaining to 197 regions in EU-15 and
Switzerland, over the time period 1978-2001 (24 years)
Descriptive statistics (per region and year, period 1978-2001)
Number of patents
Patents per population
(by million inhabitants)
Population (thousands)
Collaborations KGI-I
Collaboration I-I
Min
0
,00
Max
156
43,32
Mean
4,69
2,15
Std. Dev
10,55
4,14
26
0
0
11.118
20
19
1.963,61
,16
,14
1.607,55
,834
,879
Science-Industry interaction
and the technological performance of regions
Clustering of biotech activities in EU-15 and Switzerland (1978-2001)
1/3 of patents is concentrated within 10 regions
17 regions (8,6%) have no biotech patents; 27 (13,7%) regions have no more than 5 patents
Country
Region
France
Île de France
Germany
Oberbayern
Germany
Darmstadt
Denmark
Danmark
United Kingdom
Berkshire, Buckinghamshire & Oxfordshire
United Kingdom
East Anglia
Netherlands
Zuid-Holland
Belgium
Vlaams gewest
Germany
Karlsruhe
Germany
Köln
…
EU-15 + Switzerland (197 regions)
Cumulative amount of EPO patents (1978-2001), full count of inventor addresses
Patents
1.356
1.013
879
846
693
652
579
563
498
496
22.190
Cum %
6%
11%
15%
18%
22%
25%
27%
30%
32%
34%
Science-Industry interaction
and the technological performance of regions
Top 10 regions in EU-15 + CH
Berkshire, Buckinghamshire
and Oxfordshire(UK)
East Anglia (UK)
Denmark (DK)
Zuid-Holland (NL)
Vlaams gewest (BE)
Île de France (FR)
Köln (DE)
Darmstadt (DE)
Oberbayern (DE)
Karlsruhe (DE)
GeoDa
Science-Industry interaction
and the technological performance of regions
Collaboration within biotechnology
15.015 patents with at least 1 assignee in EU-15 and Switzerland (1978-2001)
=> 1.843 (12,3%) with 2 or more assignees

536 KGI – industry collaboration (3,6%)

409 Industry – industry collaboration (2,7%)
Correlations
Number of patents
Patents per population
Collaborations KGI-I
Collaborations I-I
Number of
patents
1
,763(**)
,615(**)
,278(**)
Patents per
population
Collaboration
KGI-I
Collaboration
I-I
1
,384(**)
,318(**)
1
,188(**)
1
** Correlation is significant at the 0.01 level (2-tailed).
Science-Industry interaction
and the technological performance of regions
Evolution of patenting in the field of biotechnology
Biotech patents: applications
5000
4500
4000
3500
3000
2500
2000
1500
1000
500
0
1978 1979 1980 1981 1982 1983 1984 1985 1986 1987 1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001
EPO Patents 1978-2001, worldwide
Period 1978-1990: steady linear increase of the patent stock
Period 1991-1999: exponential growth of the number of patents
Patents
Science-Industry interaction
and the technological performance of regions
MODEL: What is the nature and impact of university – industry collaborations for
regional development as technologies and industries progress along the
technology/product life cycle?
Biotech patents: applications
5000
Period 1978-1990:
First, explorative phase of the TLC
4500
4000
3500
3000
Period 1991-1999:
Next, more exploitation orientated
phase of the TLC
2500
Patents
2000
1500
1000
500
0
1978 1979 1980 1981 1982 1983 1984 1985 1986 1987 1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001
EPO Patents 1978-2001, worldwide
Collaboration in year t-> technological performance of the region in year t+2
Fixed Effect Negative Binomial regression model
-> controls for unobserved between region - differences such as BERD and HERD
Science-Industry interaction
and the technological performance of regions
RESULTS (1):
Number of patents per Region (t+2)
Coef.
Std. Err.
P>|z|
0,1364
0,1205
0,8655
0,026
0,017
0,072
0,000
0,000
0,000
0,0167
0,0171
0,0970
0,002
0,964
0,000
Period 1978 – 1990
Collaboration:
KGI – Industry
Industry – Industry
_constant
Number of observations
Number of groups
2158
166
Period 1991 – 1999
Collaboration:
KGI – Industry
Industry – Industry
_constant
0,0528
0,0008
1,8605
Number of observations
Number of groups
1232
176
Science-Industry interaction
and the technological performance of regions
RESULTS (2):
Number of patents per population per Region (t+2)
Coef.
Std. Err.
P>|z|
Period 1978 – 1990
Collaboration:
KGI – Industry
Industry – Industry
_constant
0,1261
0,1080
1,3200
Number of observations
Number of groups
0,0276
0,0172
0,1142
0,000
0,000
0,000
0,9187
0,0191
0,1375
0,005
0,824
0,000
2067
159
Period 1991 - 1999
Collaboration:
KGI - Industry
Industry - Industry
_constant
0,0524
-0,0042
2,0985
Number of observations
Number of groups
1232
176
Science-Industry interaction
and the technological performance of regions
CONCLUSIONS:
During the first explorative phases of the technology life cycle:
–
science – industry interaction leads to a better technological performance of the
region
–
collaboration between industrial partners contributes to the technological
performance of regions
During the more exploitative phases of the technology life cycle:
–
science – industry interaction leads to a better technological performance of the
region, suggesting that even during the later phases of the technology life cycle,
exploratory research activities remain present;
–
but collaboration between industrial partners does not lead to better technological
performance of regions: Reduced importance of collaboration between firms during
later stages of the life cycle? (<> open innovation system rhetoric)
Science-Industry interaction
and the technological performance of regions
FURTHER RESEARCH will be focused on the introduction of
-
the geographical distribution of co-patenting (local, national, international),
-
characteristics of the regional economical texture (number and size of the firms),
-
the specific role of scientific capabilities,
-
and extending indicators signaling collaboration (co-publication) in order to further
qualify the relationships identified so far