Systems view on promoting
high tech: The case of
biotechnology
Terttu Luukkonen
DIMETIC Summer school 2007
12 July, 2007
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Contents
1. Importance of conceptual framework for
research
2. Perspective of technological systems
3. Application of technological systems
approach to policy tools at national and
European level
4. Application of technological systems
approach to policy in biotechnology in Finland
5. Application of technological systems
approach to an analysis of biotechnology
commercialisation in Finland
6. Concluding remarks
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1. Importance of conceptual
framework for research
• The difference a conceptual framework
makes
• Conceptual framework vs. theory
• What is a good theory?
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2. Perspective of technological systems
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2.1: Perspective of technological
systems: what is it?
• Conceptual framework outlining important
levels and dimensions; not a theory;
however draws on theoretical perspectives
– Carlson et al., 2002
– Stankiewicz, 2002a
• Technological systems are “socio-economic networks
generating, transferring, and utilizing technologies”;
“systems are defined in terms of knowledge and
competence flows” (Carlson, p. 10)
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2.2: Perspective of technological
systems: dimensions
• Three dimensions:
– cognitive dimension defining technological
possibilities
– organizational and institutional dimension
capturing the actors engaged in the creation
of technologies.
– economic dimension defining the set of actors
who convert technological possibilities into
business opportunities and exploit them.
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2.3: Perspective of technological systems:
‘subtheories’ of the dimensions
• Cognitive dimension:
– ‘Design spaces’ by Stankiewicz:
• Organisational and institutional
– No theory
• Economic
– Eliasson & Eliasson’s competence bloc
approach
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Cognitive dimension
• Carlson et al. suggest the concept of
‘design spaces’ as outlined by
Stankiewicz: characterises
technologies/technological fields
• There are other approaches that deal
with the cognitive dimension
– Andrea Bonaccorsi’s ‘search regimes’:
characterises research fields
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Design spaces by Stankiewicz
(2002)
• Technological growth is the evolution of combinatorial search and
design spaces which are formed by clusters of complementary
technical capabilities
• As technological knowledge accumulates, the ‘raw’ search spaces
are transformed into progressively better-structured design spaces.
• Attempt:
– to describe at a very abstract level the properties of design spaces and
elements of search processes (operants, primitives, design languages)
– To outline patterns of innovative activity and call them technological
regimes: types of regimes. These determine the scope of technological
opportunities
– Highlights that ‘design spaces’ can be applied to different levels of
aggregation (dynamic growth can occur at subfield level giving rise to
new design spaces.
• Problem: difficult to operationalise
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2.4: Some criticism concerning the
technological systems approach as
outlined
• Nature as a ‘patchwork’
• The organisational and institutional dimension is too
restricted; should be more general and understand
institutions sociologically (recurrent interactions among the agents
generate new patterns of behaviour, creating new institutions or institutionalized forms of
behaviour )
• The cognitive dimension in some other approaches
(Bonaccorsi’s knowledge dynamics) includes this
restricted institutional aspect (in complementarities)
• Policies can address the different dimensions (as my
following examples will indicate). However, policy
could form a fourth dimension which attempts to
influence the other dimensions.
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Revised systems dimensions
Cognitive
dimension:
knowledge
dynamics,
Institutiona
l
dimension
Economic
dimension
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Political
dimension
3. Application of technological systems
approach to structure policy tools at
national and European level
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3.1: Application of technological systems
approach to policy tools: cognitive dimension
Dimension
Policy
objective
Cognitive
Policies at the
national level
Scientific
Traditionally
infrastructure core area of
national
research
policies:
institutional
support to
universities,
researcher
training, basic
research
projects through
Research
Councils etc.
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Policies at the
European level
Traditionally no EU
policy. However, a
break: new ERA
agency: the
European Research
Council (ERC)
3.2: Application of technological
systems approach to policy tools:
organisational dimension
Dimension
Policy
objective
Organisational Promotion of
and
spillovers,
institutional
networking &
collaboration
among diff.
institutional
partners
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Policies at the
national level
Policies at the
European level
Collaborative
research
programmes
Traditionally (since
1980s) FPs focused
on promotion of
collaborative
research. In ERA,
emphasis on
integration: new tools
to promote it (ERAnets, NoEs, TPs,
coordination of nat’l
policies)
3.3: Application of technological
systems approach to policy tools:
economic dimension
Dimension
Policy
objective
Policies at the
national level
Policies at the
European level
Economic
Technology
transfer and
turning
inventions
into
innovations
Science and
technology parks,
incubators,
provision of risk
funding through
public orgs. or
funds; framework
conditions for
technology
transfer and
venture capital
(taxation, IPR etc)
No EU policies;
exchange of
information and
experiences (e.g.
ERAWATCH);
probably more
attention in the
future
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3.4. Summary
Dimension
National level European
level
Cognitive
+
Organisational
& institutional
Economic
+
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+
+
4. Application of technological systems
approach to policy in biotechnology in
Finland
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4. 1: Few characteristics of
biotechnology
• Biotechnology includes application areas outside
human health related or pharmaceuticals sector
• Startup firms are an important platform for
experimentation
• Large firms and SMEs are in frequent mutual
collaboration (‘network company’ though there
are different organisational and business
models)
• SMEs can in practice be R&D projects
• They are heavily subsidised from public purse, in
Finland, public R&D support is important
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4.2: Cognitive dimension
Dimension
Policy objective
Policies at the national level
Cognitive
Scientific
infrastructure
Special training programmes
in molecular biochemistry
since mid 1980s;
Public support to basic
research in biotechnology
through Research Councils,
through university budgets,
special institutes of
biochemistry(/biotechnology
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4.3: Organisational and
institutional dimension
Dimension
Policy objective
Organisational Promotion of
and institutional spillovers,
networking &
collaboration among
diff. institutional
partners
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Policies at the national
level
Dedicated technology
programmes to
biotechnology by Tekes
(Finnish Funding
Agency for Technology
and Innovation)
promoting collaborative
projects among
industrial firms and
industry-university
collaboration
4.4: Economic dimension
Dimension
Policy objective
Policies at the national level
Economic
Technology
transfer and
turning
inventions into
innovations
‘Biocentres’ (science parks),
incubators, public venture
capital fund Sitra investing
especially in biotech firms,
Technology transfer
organisations advising
university researchers in
patenting
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5. Application of technological systems
approach to an analysis of biotechnology
commercialisation in Finland
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5.1: The question
• Why biotechnology industry – despite massive public
support to the field in the field in general and to the
startups in particular – has not taken off
• Luukkonen & Palmberg (2007) concentrates on the
economic dimension and draws on Eliasson & Eliasson’s
(1996) competence bloc approach in order to gain
understanding of the reasons for this performance
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5.2: Competence blocs by
Eliasson and Eliasson
• The competence bloc is a set of functional
circumstances that provide a selection mechanism
(evolutionary perspective) and may be understood as a
critical factor transforming technological opportunities
into viable businesses.
• It is defined as a minimum set of activities, to be
undertaken by competent actors /competencies
embodied in competent actors in order that firms and
industries emerge, develop and contribute to economic
growth
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5.3: Competence blocs by Eliasson and
Eliasson
•
•
•
•
•
•
Inventors who solve problems by integrating
technologies in new ways through creative combinations
(represents the supply of new technological knowledge)
Entrepreneurs, or innovators, who identify profitable
inventions and introduce them in the market,
Competent venture capitalists who recognise and
finance the entrepreneurs at a reasonable price,
Exit markets that facilitate ownership change and secure
efficient turnover of venture capital funds in the
economy, and
Industrialists who take successful innovations to
industrial scale production.
Customers
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5.4: Observations on the
competence bloc approach
• By nature an empirical generalisation
of important institutions in ICT
commercialisation
– Venture capital is a major institution to finance
experimentation with new technology
– Startups are a major experimentation platform
• In technological systems perspective, cuts
across cognitive dimension (supply of
knowledge)
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5.5: Contribution to
understanding biotechnology
• Problems in the Finnish competence bloc in
biotechnology
– Venture capital
– Lack of industrialists
• Can pinpoint areas where policy intervention might
help (or not):
– General framework conditions for promoting venture capital industry;
however, biotechnology is an especially difficult area for venture
capital; we may question whether a different type of public funding
institution might complement
– Public policy cannot influence the strategies of large companies; it can,
however, provide means for promoting firm-university interaction in
R&D. Still, it has not been sufficient to produce the expected outcome
(large companies making alliances with SMEs and universities to
commercialise inventions).
– In both aspects, the size of the country may be too small for expected
change to happen.
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5.6: Perez’ perspective on the
findings (2002)
• Helps set the findings and the relative
development stages of technologies (ICT,
biotechnology) in the perspective of long
cycles of technological development
• The emergence of institutional actors is
related to the development stage of a
technological revolution/techno-economic
paradigm
• Can provide understanding why
biotechnology commercialisation has not
taken off (no ‘big bang’ yet)
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5.6: Application of competence bloc
elements in Perez’ phases of
technological revolutions
Inventors, entrepreneurs
Industrialists
VCs
Turning
point
Maturity
ICT
Synergy
Degree of
maturity
Golden
Age
Irruption
Big-bang
Frenzy
Financial
bubble
Technoeconomic
split
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Diminishing
returns to
innovation
Next great
BIOTECH? surge
Time
Phases
Next big bang
5.7: Further observations on
biotechnology
• The biotech revolution is a myth (Hopkins et
al, 2007): productivity in drug discovery as
compared with R&D expenditures has
become lower in the past 30 years
• The validity of startup model of
commercialisation and the applicability of
venture capital in biotechnology (as
compared with ICT) has been questioned
(Pisano, 2006)
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6. Concluding remarks
• Technological systems approach is not a
theory, but a conceptual framework
outlining important dimensions and levels of
observation
• Despite the limitations in this conceptual
framework (nature as patchwork with regard
to the different dimensions; restricted
understanding of the institutional
dimension), we can gain a better
understanding of the phenomena under
study
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References
•
•
•
•
•
•
Andrea Bonaccorsi. 2005. Search Regimes and industrial dynamics of
science, paper presented at the PRIME General Conference, Manchester,
January 7-9, 2005.
Bo Carlson. 2002. Magnus Holmén, Staffan Jacobsson, Annika Rickne,
and Rikard Stankiewicz, The Analytical approach and methodology, in Bo
Carlson (ed.), Technological Systems in the Bio Industries, Kluwer
Academic Publishers, Boston/Dordrecht/London, pp. 9-33.
Gunnar Eliasson & Åsa Eliasson. 1996. ‘The Biotechnological Competence
Bloc’, Revue d’Economie Industrielle, Vol. 78, No.4, Trimestre, pp. 7-26.
Michael M. Hopkins, Paul A. Martin, Paul Nightingale, Alison Kraft, Surya
Mahdi. 2007. The myth of the biotech revolution: An assessment of
technological, clinical and organisational change. Research Policy, Vol. 36,
pp. 566-589.
Terttu Luukkonen. 2005. Variability in organisational forms of biotechnology
firms, Research Policy, Vol. 34, pp. 555-570.
Terttu Luukkonen & Christopher Palmberg. 2007. Living up to the
expectations set by ICT? The case of biotechnology commercialisation in
Finland, Technology Analysis & Strategic Management, Vol. 19, No. 3, pp.
329-349
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References, continued:
•
•
•
•
Carlota Perez. 2002. Technological Revolutions and Financial
Capital (Cheltenham, UK, Edward Elgar)
Gary P. Pisano, ‘Can Science Be a Business?’, Harvard Business
Review, vol. 84, No. 10, 2006, pp. 115-125
Rikard Stankiewicz . 2002a. The Cognitive Dynamics of
Biotechnology and the Evolution of its Technological Systems, in: in:
Bo Calrsson ed.), Technological Systems in the Bioindustries,
Boston/Dordrecht/London: Kluwer Academic Publishers, pp.35-52.
Stankiewicz, Rikard. 2002b. Design Spaces, Generic Capabilities
and Research Policy, Paper prepared for Conference on ‘Rethinking
Science Policy: Analytical Frameworks for Evidence-Based Policy’,
SPRU, University of Sussex, March 21-23, 2002.
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