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Innovation
Networks - Social Networks and the Generation of Innovations*
Innovation and Networks
Key findings of empirical research in the 1960s focused on the role of
external sources for the generation of innovations and thus, on the
importance of boundary-spanning networks. As Freeman (1991: 499)
emphasizes, they started to
demonstrate the “vital importance of external information networks and
of collaboration with users during the development of new products and
processes". And, as he continues to explain, until that time most
innovation studies were only “anecdotal and biographical or purely
technical. [. . . ] Even those economists, such as Schumpeter, [. . . ]
did not study the specific features of actual innovations in any depth".
The SAPPHO project (see Rothwell 1974; Rothwell et al. 1974) was one of
the most comprehensive empirical studies during the late 1960s which is
representative of this time’s research on innovations, although it
concentrated on only two branches of manufacturing industry, chemicals
and scientific instruments. The most important characteristics that
play an essential role for the
success and failure of innovations as identified in this project are
(as outlined by Freeman 1991: 500):
- user needs and networks,
- coupling of development, production, and marketing
activities,
- linkage with external sources of scientific and technical
information
and advice,
- concentration of high quality R & D resources on the
innovative
project,
- high status, wide experience and seniority of the
“business innovator",
- basic research.
These characteristics show the primary importance of networks and
external resources as critical factors for the success and failure of
innovations. Moreover, the results of the project already stressed the
importance of both, formal and informal networks. During the 1950s,
Carter and Williams (1957, 1959) had shown the basic character of
multiple links for what they called the “progressive" firm. Piore and
Sabel (1984) provide many examples on the role and importance of
externalities that are generated by regional networks. They have been
historically important
since the early days of the industrial revolution. As Freeman (1991:
510) summarizes, “networking is in itself an old phenomenon and
networks of suppliers are as old as industrialized economies".
Nevertheless, a major upsurge of formal and informal networks can be
realized in research and literature of the 1980s of both changes in
quantitative and qualitative character. “In quantitative terms there is
abundant evidence of a strong upsurge of various forms of research
collaboration especially in the new generic technologies [. . . ],
involving extensive international collaboration as well as national and
regional networks. There is also ample evidence of a qualitative change
in the nature of the older networking relationships which have existed
for a long time" (Freeman 1991: 507). The latter includes
sub-contracting networks, research associations, government research
and development projects (R&D-projects) and programs, computerized
data banks, and value added networks.
A new upsurge of all kinds of networks takes place with the spread of
new information and communication technologies based on internet
technologies since the late 1980s until today. This constitutes their
primary importance in what is known as the knowledge society. It is the
various kinds of information technologies that affect, through their
convergence with the telecommunication systems, the network of
communications within and between organizations, including the firm and
its supplier networks, technology networks, customer networks, etc. And
not the information technology industry itself is characterized “by
intensive technological networking for the development of its own
products, but its diffusion throughout the economy to new sectors of
application depends on the development of new networks in every sector
[. . . ]. Finally, it provides the technical means for improving
communication networks everywhere and for making them feasible in areas
where they could hardly have been introduced before. It is a networking
technology par excellence" (Freeman 1991: 509).
Social Networks in R&D-Environments
According to Jain and Triandis (1990: 21-43), R&D management should
always be guided through its business, technology, and innovation
strategies that are realized by manifold enabling mechanisms like
people, ideas, communication networks, funds, and cultural elements.
Here, we will put our focus on knowledge communication in R&D
environments through social networks in a very narrow sense.
Following the distinction of the different phases of research, Tushman
(1982: 351-352) characterizes the key features of research
projects, development projects, technical service projects and their
corresponding communication networks (as cited by Jain and Triandis
1990: 29-30). “[D]ifferent R&D activities require different
communication networks" (Jain and Triandis 1990: 31). As shown by
experience, there is an “evolution of language, concepts, values unique
to the
types of projects undertaken and, at times, unique to the organization
itself." And while this common understanding facilitates communication
with a project team (or within a densely connected network), “[t]his
local language and other characteristics make communication with the
outside—that is, beyond the organization project boundary—difficult and
prone to bias and misunderstanding" (Jain and Triandis 1990: 30; with
reference to Tushman 1982: 357). Furthermore,
following the types of relationships on the different levels of
collaboration, organizations, and individuals (as outlined by Liyanage
et al. 1999: 387-388), the networks in R&D can be distinguished
according to their level of individual, organizational, or
institutional (societal) knowledge management processes as follows (see
also Liyanage et al. 1999: 387-388):
Network
Levels
|
R&D
Process
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R&D
Objective
|
Collaborations
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Integration
|
Resource
complementary, reduce risks, pool resources
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Institutional
/ Organizational
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Linkages
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Value
creation, long range planning
|
Individual
|
Creations
|
Knowledge
creation, creativity and inquiry
|
Following
Collinson and Gregson, the “[i]nitial contacts from social networks
evolve into business-focused networks, and then into strategic
networks, which allow firms to innovate and to thrive by their links to
other organizations" (Collinson and Gregson 2003: 192; with reference
to Aldrich and Zimmer 1986; Butler and Hansen 1991; Dubini and Aldrich
1991; Falemo 1989; Flynn 1993; Johannisson 2000).
Knowledge Management and Innovation Networks
During the last two decades, the linear model of subsequent phases of
research has been abandoned in favor of recursive models (see Kline and
Rosenberg 1986). These models do not assume sequential phases anymore
(Schmoch et al. 2000: 5-7), but recursively interconnected phases that
are passed through multiple times (“multiple cycling"). This shift of
perception of the technology development process is significantly
further extended through approaches from a network perspective
(Reinhard 2001: 15). A network perspective on the technology
development process is primarily based on the Coase Williamson theory
of markets and hierarchies. Following this theory, networks differ from
other types of organizational interactions in that they achieve
co-ordination neither through market mechanisms nor through hierarchy.
Rather, social networks reach co-ordination on the normative basis of
the partners’ mutual objectively and subjectively felt advantages (see
Hakansson 1989: 15-26; Freeman 1991: 506-510). Thus, they provide a
distinct type of co-ordination mechanisms, which are especially
useful for the efficient organization of innovation activities
(Reinhard 2001: 15).
This network perspective on knowledge transfer as a type of
co-ordination that is distinct from market mechanisms and hierarchical
co-ordination proves the fundamental misconception of knowledge sharing
as so-called knowledge markets. Other authors who criticize the linear
model of research phases speak of an “interactive" or “coupling" model
of innovation (see Asheim and Cooke 1999). Collinson and Gregson (2003:
191) speak of “distributed innovation" which means “collective action
amongst firms in a distributed innovation network which cannot be
reduced to market transactions and formal contracts". Although not all
of these authors speak of networks, the various concepts of social or
organizational interaction, collaboration, and co-ordination in
innovation management imply the network perspective more or less
focused.
Looking at knowledge communication in innovation management, we can
borrow some of the insights on the knowledge management model for
knowledge flow in the R&D process as outlined by Armbrecht et al.
(2001). They share the conception of a central position of human beings
in the processes of knowledge creation and transfer. Their knowledge
flow models conceive of the complexity of interaction and suggest a
model of “a highly interpersonal and
iterative process of filtering, focusing and expanding in which the
creative process takes place" (Armbrecht et al. 2001: 32). They study
aspects of knowledge management that are unique or especially important
for the process of R&D through interviews with R&D managers and
derive therefrom a catalog of best practices. The highest priority
issues for knowledge management as mentioned in these interviews are
(Armbrecht et al. 2001: 33):
- "What kind of culture
facilitates knowledge flow and how can it best be
designed, incorporated and managed."
- "How can the knowledge of experts and people leaving the
organization
be captured."
- "What can be done to accelerate the R&D process."
- "How can the creativity envelope withing the R&D
organization be
expanded."
Social
network analysis provides not only a conceptual framework for
research on innovation
networks, but also an analytical tool for the empirical study and
support of
networks within and between organizations.
* A
comprehensive version of this text and all references can be found in
the book
presented here.
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