In Defence of the Linear Model.
An Essay
M. Balconi, S. Brusoni and
L. Orsenigo
Motivation
Widespread and criticism towards the Linear Model (LM)
Everybody agrees that the LM is wrong and useless
But then, why continuing to criticise it?
Does the LM still survive in analysis and policies?
If so, why?
Are some parts of the LM still useful?
Objectives
1)What is the LM? Can we identify the main propositions which constitute or are
usually associated to the LM in the literature?
- some brief historical remark on the origins, status and content of the LM
- V. Bush and “Science: The Endless Frontier”
2) Which are the main critiques advanced against the LM and to which context do
they apply?
3) Do these critiques really destroy the LM?
4) 3 main dimensions of the debate:
- cognitive
- organisational
- normative
5) Conclusion
Preliminary Observations
critiques of the LM encompass a variety of
different – and often mutually incompatible –
arguments and implications, which do not
necessarily derive from the model itself
the demise of the LM has opened the
Pandora’s box of possible alternative
“models” and normative prescriptions
CAVEAT
Not an historical reconstruction
Not a claim on the empirical validity of the LM
But an essay:
- not all the critiques are really destructive
- often they are uncoherent or mutually
contradictory
- the LM – in a weak form – may well survive
and be useful, at least in some domains of analysis and
policy
To begin with
• “at one time it was almost impossible to read a
book or an article on technology policy or
technological forecasting that did not begin or
end with a polemic against the so-called linear
model of innovation”
• “The LM cannot be simply dismissed as a
convenient strawman erected for the
convenience of those expounding alternative
ideas” (C.Freeman, The Greening of Technology,
1996, cited in Edgerton 2004).
Some background literature
• Did the LM ever existed?
• Or was it a straw man?
• Is it a theory? Or a model?
• A Folk Model?
• What are its main components?
Alternative interpretations
• D. Edgerton (2006): the LM did never actually exist, neither in theory nor
in practice
• A model of the relationships between science and society and specifically,
innovation and economic growth
• The term LM was rarely used before the '80s and almost always critically
• It comes in various forms and it is never very well spelled out. But its
common theme seems to be:
– basic science is the main source of innovation
– the innovative process is sequential
– Innovation is a major source of growth
• Critiques:
– the innovative process is “irrational and cannot be programmed in advance
(Price and Bass 1969)
– Innovation rarely rests on scientific research
Godin (2006)
• The model, whatever its name, has been the very mechanism used for
explaining innovation in the literature on technological change and
innovation since the late 1940s.
• The model postulates that innovation starts with basic research, then adds
applied research and development, and ends with production and
diffusion:
• The model has been very influential. Academic organizations as a lobby for
research funds (National Science Foundation 1957) and economists as
expert advisors to policy makers (Nelson 1959) have widely disseminated
the model, or the understanding based thereon, and have justified
government support to science using such a model. As a consequence,
science policies carried a linear conception of innovation for many
decades (Mowery 1983a), as did academics studying science and
technology
Godin (ctd)
•
The LM did not arise from the mind of one individual. Rather,
it developed over time in various steps:
• First were natural scientists (academic as well as industrial), developing a
rhetoric on basic research as the source for applied research or technology
(from F. Bacon, to M. Holland to W.R. Maclaurin,..);
• second were industrialists and consultants from business schools, having
been interested in science studies long before economists and studying the
industrial management of research and the development of technologies;
• third were economists, bringing forth the concept of innovation”:
production and diffusion:
• The result is a “rhetorical entity”, which gained strength and became
entrenched in discourses and policies with the help of statistics and
methodological rules for collecting data (Frascati Manual, 1963
Industrialists
•
Maurice Holland, Director, Division of Engineering and Industrial Research,
National Research Council: series of papers and a book on the importance of
research for industrial development: research as a modern method of accelerating
industrial evolution (1928-1933)
•
K. Mees (Eastman Kodak) describes the work of the development laboratory as a
sequential process: development work is “founded upon pure research done in the
scientific department, which undertakes the necessary practical research on new
products or processes as long as they are on the laboratory scale, and then
transfers the work to special development departments which form an
intermediate stage between the laboratory and the manufacturing department”
(Mees 1920)
•
R. Stevens, vice president at Arthur D. Little: United States National Resources
Planning Board report titled Research: A National Resource in 1941.
Economists
• W. Rupert Maclaurin: developed Schumpeter’s ideas,
analyzing technological innovation as a process
composed of several stages or steps. Maclaurin
constructed one of the first taxonomies for measuring
technological innovation in the literature, that led to
current indicators on high technology
• economists bringing forth the concept of innovation”:
production and diffusion: Y. Brozen, 1951, Usher 1954,
Carter and Williams 1957, Ruttan 1959, Machlup 1962,
Schmookler 1966, Scherer 1965, Mansfield 1968
Hounshell (2004)
• The LM can be considered as a system of belief, a heuristic
which simply states that the new knowledge generated by
investment in fundamental, unfettered research will, at
some point in the future, yield radically new inventions and
technologies.
• the linear model was very real in the United States at the
end of the Second World War and up to the early seventies;
• it made the case for the United States government’s
funding of scientific and engineering research at
universities
• and for R&D strategies of companies like DuPont, who
established fundamental research programs for the first
time in the American history (e.g. new nylons).
Science The Endless Frontier (V. Bush, 1945)
One would be hard-pressed to find anything but a rudiment of the LM model in
Bush’s manifesto.
Bush talked about causal links between science (namely basic research) and
socioeconomic progress, but nowhere did he develop a full-length argument
based on a sequential process broken down into its elements or that suggests a
mechanism whereby science translates into socioeconomic benefits.
Bush was making an argument for science policy, not for innovation (Edgerton):
- support to public funding of academic research
- basic science should be unconstrained and it will lead to innovation
Bush participated into the rethoric that basic research leads to applied research
(Godin)
The LM according to V. Bush
1) technological innovation and economic development are based on new
scientific knowledge
- Examples: health care and defence, where discoveries (such as penicillin
and radar) often arose from remote and unexpected source
- XXth century  basic research has become ‘the pacemaker of technological
progress
2) A distinction is drawn between basic and applied research, based upon the
interest in practical ends and a continuum of activities are identified between
these two research orientations
3) the centres of basic research are identified with colleges, universities and
research institutes ‘where scientists may work in an atmosphere which is
relatively free from the adverse pressure of convention or commercial necessity’
4) Since science is considered a proper concern for government (…the new
frontier..), government had to support basic research
5) Government can promote industrial research also by providing suitable
incentives to industry to conduct research, and by strengthening the patent
system. In addition, ways should be found to spread the benefits of basic research
to industries which do not now utilize new scientific knowledge.
The LM referred to by the literature (the LM in Strong Form)
Basic research  Applied Research  Development  Production
Marketing  Diffusion
•a straitjacket, which deprives Bush’s arguments of any historical references
and transforms them into an oversimplified model of the innovation process
The conventional presentation: the process and the
cognitive dimension
 Since prior scientific research is the main source of new technologies,
innovations can be considered as practical applications of basic scientific
research
New knowledge acquired through basic research trickles down, almost
automatically, to applied research, technology and innovations, even
within short time spans
the innovative process can be represented and conceptualised as sequence
of steps
 In the sequence there is no feedback from later steps to earlier steps
The actors and the organisational dimension
• 1) There is a clear division of labour along the sequence between
different types of agents who specialise in the various relevant
stages:
– scientific research is conducted in universities and public laboratories
– Technological development is carried out by firms:
– universities contribute to applied research (innovation) primarily
through the conduct of research and teaching. Direct interaction with
industry is not perceived to be a fundamental mission of universities
• 2) universities and firms respond to different types of motivations
and incentives.
– Universities: public interest, the welfare of the society, individual
prestige, fame and career, ‘publish or perish’.
– Firms are driven by the quest for profit.
The conventional presentation: normative
prescriptions
• basic research – and therefore the agents
performing it, typically universities - should be
funded by public sources
• new knowledge has to be placed in the public
domain.
• applied research – typically performed by
business firms – should not in principle be
supported by the government, at least to the
extent that its output can be appropriated and
protected by imitation.
The critiques to the LM: the cognitive dimension
1) The relationship between science and innovation
• the distinction between basic and applied research is not clearcut (e.g. Stokes, Dasgupta and
David)
• most technological improvements are unrelated to basic research and they often
anticipate science  …after the WW2 incremental technological innovation
remained extremely important (Kline and Rosenberg)
• not only is technology independent of new science, but it also provides
essential inputs to scientific research (problems to be solved, instrumentation)
• the conventional time orientation and direction of causation of the model
should be reversed in many cases
• users of products and processes are the developers of many important innovations
that are later produced and sold by manufacturers (von Hippel, the mountain bicycle
(Lüthje et alii, 2005))
 ‘An Overview of Innovation’, Kline and Rosenberg , 1986
There is a tendency to identify technological innovation with major innovations
…The fact is that much technological change takes the form of very small
changes, such as minor modifications in the design of a machine…
Most innovation is done with the available knowledge already in the heads
of the people doing the work …It is only when those sources of information
fall short of solving the problem that there is a need for research in order
to complete a given innovation…The notion that innovation is initiated
by research is wrong most of the time…
According to KR the initiating step of most processes of technological
transformation in today’s world is typically design rather than research
This stream of critiques does not destroy the LM, but drastically
reduces the sphere to which it can be applied
However:
 it is often argued that in the XX century the emergence of major new
technological paradigms has frequently been directly dependent and
directly linked to major scientific advancements
others claim that in the two or three last decades the role of science as
a major source of innovation and as a driver of the expansion of high tech
industries has further increased
We don’t know, but:
 in knowledge intensive sectors scientific advance - remains
extremely important and sometimes the initiating point of the
process of innovation, often with long temporal and cognitive lags
 Basic research increases research productivity (Nelson, 1959;
Mowery and Rosenberg, 1998).
basic research does not necessarily coincide strictly with “pure
science”: e.g. vaccines and most biomedical research.
If the distinction between basic and applied research is blurred, why
not simplifying the LM, instead of complicating it? (Stokes, user
inspired basic research)
• user-developed innovations: niche products and highly sophisticated
customers (mountain biking, surfing enthusiasts or surgeons etc.), in
situations where the interplay between technical performance and
practice is paramount. And in most cases, these customer-driven
innovations rely on well established science (e.g. applications of new
materials to surf boards)
• science and technology are not perfectly malleable to economic
and social signals (Dosi, 1982).
• According to a “weak” LM:
 basic research (and scientific advances) are
neither necessary nor sufficient for innovation
to take place, but remain very important
The critiques to the LM
2) Bottlenecks, feedbacks, interconnections
•
knowledge does not flow smoothly among different stages of the innovative
process and among different organisations and institutions or geographical
areas (tacitness, need of incentives)
•
But the LM may easily accommodate for the existence of impediments to the
flow of knowledge. In fact, one might argue that it is exactly the use of a linear
representation of the innovation process which has enabled researchers to
identify bottlenecks.
• Technological progress is interactive in nature  CHAIN LINKED
MODEL
• Given the fundamental role of design in triggering innovation, KR
(1986) criticise the sequentiality of the process of technological
change, stressing that the activities involved occur simultaneously
and/or with continuous feedback among them
• A constellation of concomitant tasks, instead of a sequence
• This challenges the very notion of linearity
It is (correctly) destructive only of the strong form LM (and it applies mainly
to incremental innovations)
Is the LM is a model of the innovation process performed within individual
firms?
Or a model which applies at the macro level and considering the long run?.
 When considering science-based sectors such as biotechnology, we do not
find so often the occurrence of concomitant tasks
In sectors where the outcomes of basic research take a decade to reach the
market, feedback from users will impact on current or future research
projects, but cannot influence the research carried out a decade earlier
(drugs, …)
Before applying something, this something needs to exist
At a more theoretical level:
1) A process may exhibit feedback loops but remain linear: many linear systems
exist in theory and in practice.
2) The fact that various components interact does not imply that they are
completely and fully interconnected, and thus need to unfold in parallel. A system
or a network can be partially decomposed in subsystems, linearly connected
to each other.
3) There can also be different structures that cannot be classified simply
into the two extreme forms.
4) Fully connected systems are very unstable systems and partitioning pays off
in terms of stability, predictability and sheer manageability (project management
builds on a linear sequence).
5) Danger: everything depends on everything else
6) Perhaps the LM can still be usefully applied at least within specific
subsystems in some technologies
The critiques to the LM
3) The organisational/institutional dimension
Systems of innovation literature (national, regional, sectoral)
• there is a large variety of organisations, both public and private, that contribute
to the generation of technological innovation
• a large variety of institutions (the financial system, laws and practices governing
labour markets, etc.)
• the relations and interactions among the various actors are crucially important
 Not at odds with the LM:
even within a system, significant relationships among agents may remain linear
the critiques of the LM may have gone too far: they focus attention too much on
relationships rather than on the properties and characteristics of the individual
components (nodes) of the system (network).
A network is a network is a network …..
Systems and network theories are a language: everything can be represented as a
system or a network
Thus, it it is necessary to specify very carefully and in detail, the structure of any system
or network under observation
Often, networks and systems have a a hierarchical nature
The critiques to the LM
4) The normative dimension
The LM does not bear any strong and obvious normative implication
(If anything, the LM suggests the public support of basic, unfettered, research)
Critiques:
-At the micro level (firm’s strategies and organisation)
-At the macro level : From science policy to innovation policy
The micro level
• Decentralisation of R&D
• Promoting dense knowledge flows within the
firms and across different types of
organisations
• But:
– Not necessarily at odds with the Weak LM
– Need to strenghten integrative capabilities
The Macro level
• The third mission of universities (Triple Helix, the European
Paradox, …)
• Implication: closer and flexible interaction among universities, firms
and intermediate organisations should be promoted: transfer of
knowledge
• institutions should be created to facilitate these exchanges
• Basic research should be exploited more aggressively for economic
and social applications
• Not necessarily at odds with the LM  basic research comes first,
but it does not trickle down
• Different arguments for justifying (alternative)
normative prescriptions:
Basic research too remote from application
different sets of incentives (Dasgupta and David)
Tacitness
knowledge as information, partial appropriability
Mode II: scientific research has become increasingly
multidisciplinary and involves different types of
institutions, techniques and methods (Gibbons et al.,
1994).
But: Continuing relevance of disciplinary based
research: who pays for the overheads?
See David vs. Kealey: these prescriptions can be
sustained or criticised on the basis of the LM
Conclusions
a) Basic research and science continue to be a fundamental – although certainly not
unique – source of technological advance
b) Frictions in the knowledge flow can be easily accomodated for in the LM
c) Systems can be linear or linearly decomposed; the structure of the relevant
networks must be clearly identified
d) Time is irreversible
e) Multiplicity of agents in the innovative process can be easily accomodated for in
the LM
f) As such, the LM does not imply strong normative prescriptions
g) But critiques to the LM are used to support widely different suggestions and they
are often mutually inconsistent; perhaps, the advocacy of stronger linkages among
agents is even more compelling in the context of a weakened LM
Conclusion (2)
• Either the LM is dead (or it never existed): then stop
criticizing it
• Or it is still alive in a weak form: why and where?
• The LM in Weak Form might still be useful:
– for understanding a subset of technologies, industries,
activities
– at a sufficiently high level of aggregation and/or over
sufficiently long time horizons
– As a conceptual tool for understanding and managing
complex structures and relationships
• Alternative models are often as generic as the LM
– It is important to specifify and strengthen them
EMPIRICAL EXAMPLES:
Fields very different with regard to the level of maturity and basicness of
their scientific knowledge foundation
Biotechnologies
 limited knowledge of the human biological systems and processes
the creation of new drugs particularly uncertain and risky
innovation starts with fundamental, basic research
Microelectronic circuits design
Based on the advancements in knowledge along a well established trajectory
 creating circuits with new functionalities or very substantial cost reductions is
very complex
this task involves long term, scientific commitment academic engineering
research
In both cases:
 the starting point of the innovation process is the result
of recent scientific endeavour conducted ‘far from the adverse pressure
of commercial necessity’
Distance from the market is the premise for delivery of the most
important innovations
Heavy interaction between the R&D and marketing departments of firms,
or the yielding of research to pressure from firms to satisfy clients’ needs,
stifles innovation
An essential sequentiality of tasks and a clear rationale for the division of labour
between university and industry is required
Universities
Understanding laws of nature
Serving human needs
Use inspired basic
research
Industry
Opportunities for
new drugs
MARKET
Development into
marketable products
Feedback: new research
Time (years)
t
t +3
Feedback: new research
t + 10
It is possible to progress to the next step only when the previous problem has been
solved
basic research  target  hit  lead  proof of concept
 in vitro experimentation  in vivo experimentation
Given the long time between basic research and clinical trials, feedbacks are hardly
concomitant
Evidence from products impacts on basic research with long lags
Network of agents: highly hierarchical and with a distinct orientation
 younger, smaller companies tend to be the originators of projects which are
developed by older firms
Universities, collaborating
with industry
Industry
Advances along technological
trajectories open new
unexplored opportunities
Understanding the functioning
of artefacts
Exploring new opportunities
Solving technological puzzles
Technology-inspired research
protected from market pressures
Time (years)
Explored
opportunities
Development into
marketable products
MARKET
Feedbacks:
new research,
new development
b) free and open scientific research, not stifled
by near term market demands,
is absolutely crucial to serve the long term
needs of the economy and
of society
(c) there is, as a consequence, a fundamental
virtue in the division of labour
between public research and industry, which
should be protected, not threatened;
(d) public support of basic, scientific research
is and should remain a crucial
concern of governments for both economic
and many other social and
cultural reasons