In Defence of the Linear Model: An Essay

In Defence of the Linear Model.An EssayM. 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 • 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 • 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))

 ‘AnOverview 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 Basic research and science continue to be a fundamental – although certainly not unique – source of technological advance Frictions in the knowledge flow can be easily accomodated for in the LM Systems can be linear or linearly decomposed; the structure of the relevant networks must be clearly identified Time is irreversible Multiplicity of agents in the innovative process can be easily accomodated for in the LM As such, the LM does not imply strong normative prescriptions 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 • Microelectroniccircuits 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 Industry Understanding laws of nature Serving human needs Opportunities for new drugs Use inspired basic research Development into marketable products MARKET Feedback: new research Feedback: new research Time (years) t t + 3 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 Explored opportunities Technology-inspired research protected from market pressures Development into marketable products MARKET Feedbacks: new research, new development Time (years)

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

In Defence of the Linear Model: An Essay