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Diagram 1: Dimensions of the innovation system
Low technology sectors
High technology sectors
DUI-mode of innovation
1
2
STI-mode of innovation
3
4
There is a tendency in the innovation literature to assume that only cells 1 and 4 are relevant and
among innovation policy makers there is a tendency to focus most of the attention on cell 4. We see
both as examples of bias. The reason why orgware and socware are so important for the
performance of the innovation system – for the transformation of technical innovation into
economic performance - is that they are crucial for what is going on in cells 1 and 2. Cell 3 is also
important to take into account since, in the current phase, it often refers to missing linkages and lack
of effective demand among firms.
At this stage I will argue that the distinction between the two modes of innovation is useful when it
comes to define the borders of the innovation system. Later on I will show that the two modes of
innovation are highly complementary.
National systems of innovation may be defined in evolutionary terms with reference to how
different national systems create diversity, reproduce routines and select firms, products and
routines. It is also obvious that a focus on co-evolution of production structure, technology and
institutions is useful when it comes to understand the historical transformation of national
innovation systems. I would argue though that the most important reason for seeing NSI as an
evolutionary concept is the strategic role it gives to knowledge and learning. The analysis of
innovation systems may be seen as an analysis of how knowledge evolves through processes of
learning and innovation. As I see it the assumptions forming the core of the concept are the
following:
A first assumption is that elements of knowledge important for economic performance are localized
and cannot easily moved from one place to another.
A second assumption is that important elements of knowledge are embodied in the minds and
bodies of agents, in routines of firms and in relationships between people and organizations.
A third assumption is that learning and innovation is best understood as the outcome of interaction.
Perhaps the most basic characteristic of the innovation system approach is that it is ‘interactionist’.
6
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Actually the NSI-approach has elements in common with the social psychological pragmatist school of Chicago and
not least with the ideas of George Herbert Mead and John Dewey.
11
A fourth assumption is that interactive learning is a socially embedded process and that therefore a
purely economic analysis is insufficient.
A fifth assumption is that learning and innovation are strongly interconnected (but not identical)
processes.
A sixth assumption is that national systems differ in terms of specialization both in production and
trade and in terms of knowledge base.
A seventh assumption is that national systems are systemic in the sense that the different elements
are interdependent and that interrelationships matter for innovation performance.
Box 2: Is the National System of Innovation an Evolutionary Concept?
National systems of innovation may be defined in evolutionary terms with reference to how different national systems
create diversity, reproduce routines and select firms, products and routines. It is also obvious that a focus on co-
evolution of production structure, technology and institutions is useful when it comes to understand the historical
transformation of national innovation systems. I would argue though that the most important reason for seeing NSI as
an evolutionary concept is the strategic role it gives to knowledge and learning. The analysis of innovation systems may
be seen as an analysis of how knowledge evolves through processes of learning and innovation. As I see it the
assumptions forming the core of the concept are the following:
A first assumption is that elements of knowledge important for economic performance are localized and cannot easily
moved from one place to another.
A second assumption is that important elements of knowledge are embodied in the minds and bodies of agents, in
routines of firms and in relationships between people and organizations.
A third assumption is that learning and innovation is best understood as the outcome of interaction. Perhaps the most
basic characteristic of the innovation system approach is that it is ‘interactionist’.
7
A fourth assumption is that interactive learning is a socially embedded process and that therefore a purely economic
analysis is insufficient.
A fifth assumption is that learning and innovation are strongly interconnected (but not identical) processes.
A sixth assumption is that national systems differ in terms of specialization both in production and trade and in terms of
knowledge base.
A seventh assumption is that national systems are systemic in the sense that the different elements are interdependent
and that interrelationships matter for innovation performance.
Most of these ideas were hinted at already in the introduction to Lundvall (1992) where it was stated that ‘the most
important resource in the economy is knowledge and the most important process is learning’. But at that time the ideas
were presented in an intuitive and crude form. Basically the references to knowledge and learning were still presented
as ‘black-box’ concepts and at best they could be seen as ‘finger-posts’ indicating future research agendas.
7
Actually the NSI-approach has elements in common with the social psychological pragmatist school of Chicago and
not least with the ideas of George Herbert Mead and John Dewey.
12
Most of these ideas were hinted at already in the introduction to Lundvall (1992) where it was
stated that ‘the most important resource in the economy is knowledge and the most important
process is learning’. But at that time the ideas were presented in an intuitive and crude form.
Basically the references to knowledge and learning were still presented as ‘black-box’ concepts and
at best they could be seen as ‘finger-posts’ indicating future research agendas.
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