192 L. M. Dybdahl and E. J. Iversen
centres can be a source of innovation and change (Nelson, 1993). The variety
of connections among actors influences the dynamics in the innovation
system. New knowledge can result in novel links with other innovation
systems, stimulate the entry of new actors and institutions and alter the system
boundaries (Malerba & Adams, 2015). The heterogeneous area of nanotechnology is another example where new knowledge and techniques help to
promote innovation in a range of existing industrial contexts. Knowledge
transfer across cross- sectorial connections can lead to transformation processes
in sectoral systems (Malerba, 2005). This suggests a cross- sectoral perspective
which we argue is particularly germane to the so- called bioeconomy. We
therefore invoke the Sectoral Systems of Innovation (SSI) perspective, which
serves to ‘focus on systemic features in relation to knowledge and boundaries,
heterogeneity of actors and networks, institutions and transformation’
(Malerba, 2005, p. 398).
The systems approach is useful for designing policies which support the
stimulation of a sector. The development of a meta- sector like the bioeconomy is guided by knowledge- based processes which help to direct ‘the patterns of firms’ learning, competencies, behaviours, and organisation of
innovative and production activities in the sector’ (Malerba, 2004, p. 23).
Governments play a key role in the absence of existing markets. They are
seen as critical in promoting learning and innovation by promoting research
and innovation across the boundaries of economic sectors of universities and
other higher education institutions (HEIs), public research organisations
(PROs) and the full range of relevant private and non- private entities. These
can help existing knowledge systems to reorganise themselves in ways that
can promote the creation and sharing of new knowledge within the sector. In
addition, this type of dynamic may beget new sectoral institutions and organisations (such as research centres or new educational fields), creating more
knowledge variety, which again can influence the evolution of a sector
(Nelson & Rosenberg, 1993).
A current focus of the innovation studies landscape is on improving the
coordination of existing and emerging knowledge of different types in order
to address what are known as ‘societal challenges’, i.e. challenges that primarily involve social payoffs rather than individual payoffs and which involve
systemic change in which public policy is expected to play a more central and
coordinative role. The literature has more recently recognised the new role
that knowledge can play in addressing the societal challenges of the 21st
century (Bessant & Venables, 2010) as well as the roles that public policy can
play in this process.
What individual actors know and how they learn is thus a key component
of any innovation- oriented system. This includes both new and existing types
of knowledge, processes of creation as well as coordination, and theoretical as
well as more practical types of knowledge. Components of knowledge are
one dimension of this picture, in terms of what economic actors know. In
addition, the way that the knowledge processes are organised across existing
centres can be a source of innovation and change (Nelson, 1993). The variety
of connections among actors influences the dynamics in the innovation
system. New knowledge can result in novel links with other innovation
systems, stimulate the entry of new actors and institutions and alter the system
boundaries (Malerba & Adams, 2015). The heterogeneous area of nanotechnology is another example where new knowledge and techniques help to
promote innovation in a range of existing industrial contexts. Knowledge
transfer across cross- sectorial connections can lead to transformation processes
in sectoral systems (Malerba, 2005). This suggests a cross- sectoral perspective
which we argue is particularly germane to the so- called bioeconomy. We
therefore invoke the Sectoral Systems of Innovation (SSI) perspective, which
serves to ‘focus on systemic features in relation to knowledge and boundaries,
heterogeneity of actors and networks, institutions and transformation’
(Malerba, 2005, p. 398).
The systems approach is useful for designing policies which support the
stimulation of a sector. The development of a meta- sector like the bioeconomy is guided by knowledge- based processes which help to direct ‘the patterns of firms’ learning, competencies, behaviours, and organisation of
innovative and production activities in the sector’ (Malerba, 2004, p. 23).
Governments play a key role in the absence of existing markets. They are
seen as critical in promoting learning and innovation by promoting research
and innovation across the boundaries of economic sectors of universities and
other higher education institutions (HEIs), public research organisations
(PROs) and the full range of relevant private and non- private entities. These
can help existing knowledge systems to reorganise themselves in ways that
can promote the creation and sharing of new knowledge within the sector. In
addition, this type of dynamic may beget new sectoral institutions and organisations (such as research centres or new educational fields), creating more
knowledge variety, which again can influence the evolution of a sector
(Nelson & Rosenberg, 1993).
A current focus of the innovation studies landscape is on improving the
coordination of existing and emerging knowledge of different types in order
to address what are known as ‘societal challenges’, i.e. challenges that primarily involve social payoffs rather than individual payoffs and which involve
systemic change in which public policy is expected to play a more central and
coordinative role. The literature has more recently recognised the new role
that knowledge can play in addressing the societal challenges of the 21st
century (Bessant & Venables, 2010) as well as the roles that public policy can
play in this process.
What individual actors know and how they learn is thus a key component
of any innovation- oriented system. This includes both new and existing types
of knowledge, processes of creation as well as coordination, and theoretical as
well as more practical types of knowledge. Components of knowledge are
one dimension of this picture, in terms of what economic actors know. In
addition, the way that the knowledge processes are organised across existing