The Competitiveness of Nations in a Global Knowledge-Based Economy
Partha Dasgupta [a] and Paul A. David [b]
Toward a new economics of science
Policy Research, Vol. 23, 1994, 487-521
a - Cambridge University, Cambridge, UK
b - All Souls College, Oxford
University, Oxford OX) 4AL, UK
Content
Abstract
1. Introduction and motivation: Science, economics and politics
2. The old economics of basic research, and the emergence of a new
economics of science
3. Knowledge: Codified or tacit? Public or private?
3.1. Knowledge, information, and the endogeneity
of tacitness
3.2. Science and Technology: Public and private knowledge
4. Priority and adherence to the norm of disclosure in the reward
system of science
4.1. Priority and the science reward system
4.2. Priority and secrecy in Science: Public virtue and private vices
4.3. Culture: The enforcement of cooperative rivalry and collective
regulation in Science
5. Resource allocation within scientific fields and programs
6. The timing of research programs within Science
7. Policy challenges: Maintaining Science and Technology in dynamic
balance
7.1. Capturing the training and screening externalities generated by
open science
7.2. Managing competition for scientists between complementary research
activities
7.3. Promoting greater ‘industrial transferrability’
of university research findings
8. Conclusion
9. Acknowledgements
10. References
Page 1
Science policy issues
have recently joined technology issues in being acknowledged to have strategic
importance for national ‘competitiveness’ and ‘economic security’. The economics literature addressed
specifically to science and its interdependences with technological progress
has been quite narrowly focused, and has lacked an overarching conceptual
framework to guide empirical studies and public policy discussions in this
area. The emerging
‘new economics of science’, described by this paper, offers a way to remedy
these deficiencies. It makes use
of insights from the theory of games of incomplete information to synthesize
the classic approach of Arrow and Nelson in examining the implications of the
characteristics of information for allocative
efficiency in research activities, on the one hand, with the functionalist
analysis of institutional structures, reward systems and behavioral norms of
‘open science’ communities - associated with the sociology of science in the
tradition of Merton - on the other.
An analysis is presented of
the gross features of the institutions and norms distinguishing open science
from other modes of organizing scientific research, which shows that the
collegiate reputation-based reward system functions rather well in satisfying
the requirement of social efficiency in increasing the stock of reliable
knowledge. At a more fine-grain level of
examination, however, the detailed workings of the system based on the pursuit
of priority are found to cause numerous inefficiencies in the allocation of
basic and applied science resources, both within given fields and programs and
across time. Another major conclusion,
arrived at in the context of examining policy measures and institutional reforms
proposed to promote knowledge transfers between university-based open science
and commercial R&D, is that there are no economic forces that operate
automatically to maintain dynamic efficiency in the interactions of these two
(organizational) spheres. Ill-considered
institutional experiments, which destroy their distinctive features if
undertaken on a sufficient scale, may turn out to be very costly in terms of
long-term economic performance.
1. Introduction and motivation: Science,
economics and politics
To say that economic growth
in the modern era has been grounded on the exploitation of scientific knowledge
is to express a truism. To say that what
goes on within the sphere of human activities identified as ‘The Republic of
Science’ has grown too important for the rest of society to leave alone is also
something of a commonplace assertion. [1] Most of the industrial nations and many
among the developing countries today acknowledge this, and virtually all
societies in which modern science is practiced pay at least lip service to the
belief that it is important to pursue some form of ‘science policy’.
Indeed, in the West
national science policies have tended to become more strongly interventionist
and more explicitly committed to ‘planning and management’. This is particularly so in the US and Great
Britain, where the remarkable post-World War II autonomy of Western science
communities in setting their own basic research agendas has undergone significant
erosion since the end of the 1960s. To
the fears of the public about scientific discoveries that may open the way to
the creation of pernicious technologies, and the continuing calls for the
exercise of greater ‘social responsibility’ on the part of concerned
scientists, have been added two more recent arguments for closer governmental
direction and control over publicly supported science. One is the generic demand for the application
of fiscal restraint to a noticeably large category of expenditures, arising more
from obsession with control-
1. For the origin of the term in quotes and its significance here, see Polanyi (1962) and note 5, below
ling government budget deficits than from any
significant real growth in the volume of public funds being devoted to civilian
R & D. [2] The other, however,
reflects the more specific concerns of politicians and government administrators
that the publicly supported parts of the scientific establishment were not
addressing their efforts to the solution of national needs, and a growing
conviction that the time had come to curtail the impulse of basic research
scientists to ‘pursue knowledge for its own sake’ in order to redirect
researchers to work on ‘applied’ projects that would bring more immediate discernable
economic pay-offs. [3]
There is no little irony in the
situation that consequently now presents itself. Supporters of political regimes that are
ostensibly hostile to centralization and government planning in economic
affairs, while jubilant over the comparative success of market capitalism and
the manifest dysfunctions of socialist and communist systems, seem eager to
subscribe to quite another position in so far as the management of science by
the state is concerned; they view with deepening suspicion the largely
autonomous, highly decentralized system for allocating resources that has been
institutionalized and has flourished within ‘the Republic of Science’. [4] Perhaps because demands for closer management control over
government-funded science and engineering research to improve its social
payoffs do seem discordant when emanating from circles that, in other contexts,
are instinctively doubtful of the public sector’s capability to allocate scarce
resources efficiently, the idea of bringing the work of academic researchers
into closer connection with market-oriented industrial R&D projects has
lately been gaining a remarkable degree of support.
Thus, we in the West seem to have come
full circle, and are approaching from a new direction the case for re-examining
the institutions, organizational structures, and policies that constitute the
mechanisms of resource allocation in that vital sphere of social activity we
call Science. The popular press in the
US has moved beyond its earlier mode of sympathetically reporting new conquests
on Vannevar Bush’s ‘endless frontier’ of science (see
Nelkin, 1987), along with speculations about the
revolutionary consequences of such discoveries for our conception of the cosmos
and the place of mankind within it, for the progress of industrial technology
and health care, or for the sophistication and destructiveness of warfare. Instead, the newspapers increasingly divulge
the more problematic aspects of the political economy of organized science,
including some heated controversies over the criteria being used, to select
among alternative science ‘projects’.
2. In the US, federal funding for civilian R&D in 1990 was only 3.7%
larger, in constant (1982) dollar terms, than it had been in 1980, even though
on a current dollar basis this expenditure item had swelled by 56.3% during
the same period, to reach the $23.1 billion mark. However, total US expenditure for academic
R&D, which in 1990 amounted to two-thirds of federally funded civilian
R&D, had grown substantially more rapidly (in constant dollar terms) than
the latter during the 1980s - having increased by 69.3% in real terms between
1980 and 1990 (see National Science Board (1991), Appendix Tables 4-17 and
5-1).
3. In Time Magazine for 23 November 1992, Walter Massey, then
director of the National Science Foundation, is quoted as saying: “The public
hears that we’re No. 1 in science, and they want to know why that fact isn’t
making our lives better. The one thing
that works in this country doesn’t seem to be paying off.” The story goes on to point out that the shift
underway in the US government’s stance towards science was not the product of
the new administration. “Long before the
[presidential] election, policymakers were concluding that they should assert
more control over research by telling many scientists precisely what to work
on. ‘We’ve got to do some readjusting’,
says Guyford Sever, co-chairman of a recent Carnegie
Commission study on the future of American science.” see Thompson (1993) p. 34.
4. To appreciate fully the irony in this, one need only read the
following extract from a well-known critique of the outcome of the enormous
growth of a science establishment supported by the State and large business
corporations:
… as these developments have proceeded in a uncoordinated
and haphazard manner, the result at the present day is a structure of appalling
inefficiency both as to its internal organization and as to the means of application
to the problems of production or welfare. If science is to be of full use to society it
must first put its own house in order.
The author was not a businessman taking his turn at bat as a member of
the Reagan-Bush ‘teams’, nor a populist investigative congressman, out to
expose the abuses of academic research institutions, nor a science advisor or
minister in the Thatcher government. Rather,
the passage is quoted from The Social Function of Science [10, p. xiii]
by J.D. Bernal - a scientist and Marxist historian of science and technology,
who took a leading role in the ‘social relations of science’ movement in
Britain during the 1930s!
488
For example, has the US
Congress been successfully lobbied to spend excessive sums on enterprises in
‘big science’, like the superconducting supercollider, at the sacrifice of a myriad undertakings in ‘little science’? Should we be trying to launch extensive,
publicly funded programs like the effort to sequence the human genome, as soon
as techniques and instrumentation that permits such research become available? Or, should some lines of investigation be
deferred in favor of others? Should the
availability of supplementary state and local government subsidies be made a
deciding consideration when the National Science Board selects among groups of
academic researchers (located at competing sites) those who are to receive the
bulk of funds allocated for a particular scientific sub-field? Are public and private monies being channelled excessively into some fields of basic research,
while other, potentially fruitful areas remain virtually drought-stricken? Is the amount and distribution of public
funding for university laboratories insufficient to permit them to keep pace
with rising costs of state-of-the-art equipment, such as is made available to
researchers in industry?
Still other news reports
reflect growing recognition of the subtle and complex issues facing those who
must frame science policies affecting the conduct of basic research in an
environment of global economic competition. Why should any nation continue to devote a
significant portion of its public expenditure to advancing scientific knowledge
if, through the global networks of the international science community, those
new discoveries soon will be made available to allies and rivals alike? How can one tell whether or not it is on
balance advantageous for a particular country to have its scientists
participating in a unrestricted exchange of
information with colleagues working abroad? Is the US failing to provide graduate
(research) training for its nationals in the natural sciences, mathematics, and
engineering, while at the same time subsidizing such training for too many
foreign nationals? What is it about
research universities that creates barriers impeding the easy and rapid
‘transfer’ of new scientific knowledge to the sphere of commercial applications
- even in the US, where cultural traditions of academic separation from the
world of business affairs are far less strong than remains the case in western Europe? To
what extent is it desirable to modify modern university institutions and
operating rules to permit and encourage closer integration of academic and
corporate research activities? Is it a
legitimate cause for national concern when foreign corporations actively
recruit university scientists to staff company-run basic research institutes
set up in their immediate vicinity (as was the case when a computer science
research institute under Japanese corporate management was located on the
doorstep of the University of California in Berkeley)? Would there be no equivalent cause for concern were the business corporations American in
ownership? [5]
It is thoroughly
understandable why economists have remained much preoccupied with theoretical
and empirical studies of the sources of technological innovation and its
connections to productivity growth and improvements in economic well-being and
national economic power. At the same
time, in the present setting, it is a surprising and rather regrettable fact
that elaboration of the economic analysis of technology was for some time
allowed to run far ahead of the economics of science. In the following pages we undertake to report
on recent analytical developments that may enable the laggard member of the
pair to catch up, and which hold out the prospect that the two naturally
interrelated areas of study can begin moving forward more swiftly in tandem. Our economic analysis of the organization of
research within the spheres of science and technology emphasizes the point that
we are dealing with an interrelated system, comprised of distinct activities
that may reinforce and greatly enrich one another, but, furthermore, that it is
a system that remains an intricate and rather delicate piece of social and
institutional machinery whose con-
5. For a sample of recent reporting of some of these issues, see:
Japanese Labs in U.S. Luring America’s Computer Experts, New York Times, 11
November, 1990; Graduate Schools Fill With Foreigners, New York Times, 29
November, 1990; Foreign Graduate Students Know Hardship, New York Times, Letters,
13 December 1990; William J. Broad, Big Science - Is it Worth the Price?, New
York Times, Feature Series, 27 May, 29 May (on superconducting supercollider),
5 June (human genome project), 10 June (NASA space station project), 19
June (NASA earth observing system project), 4 September (small-scale basic
science funding impacts), 4 October (hot fusion project), 25 December 1990
(cutbacks funding for big science projects).
stituent elements also may become badly misaligned. Indeed, there does not seem to be an adequate
appreciation of the vulnerability of the science-technology systems in the West
today, for all the frequency with which their importance to the modern economy
and polity is acknowledged; nor of the basic features that are common to these
variegated institutional and cultural structures, and which render all of them
susceptible to destabilizing and potentially damaging experiments which may
soon be embarked upon in the earnest hope of more fully mobilizing the
respective national scientific research communities in the service of national
economic security - the successor goal to military security - that is now being
promoted under the euphemism of ‘competitiveness’. Of course, the best preventative against blind
and costly social experimentation that we can recommend is a prior investment
in acquiring and disseminating deeper scientific understanding of the subject
of concern. That, precisely, is our
purpose in the present article.
2. The old
economics of basic research, and the emergence of a new economics of science
We must begin by
acknowledging that it would hardly be fair to charge economists with having
simply ignored problems of resource allocation in relation to science. Before there could be a new economics of the
subject there must have been an ‘old’ economics of science, and so there was. The emergence of ‘shortages’ in the market for
scientific and engineering personnel attracted the attention of economists
(e.g. Blank and Stigler, 1957; Arrow and Capron, 1959) early in the
post-Sputnik era, and the literature that subsequently expanded on the economic
determinants of the flow of newly trained scientists and engineers was greatly
enriched by applications of concepts and empirical methods from the theory of
human capital. Moreover, the seminal
contributions to the modern analysis of the production and distribution of
basic scientific knowledge date from the same period, notably the analytical
work of Nelson (1959) and Arrow (1962), on the implications of the difficulties
of privately appropriating the economic value of basic research findings. Closely related to those developments in the
literature are the sequels to Griliches’ (1960)
pioneering empirical effort in quantifying the economic ‘spillovers’, or
‘un-appropriated social benefits’ that might flow to society at large from
science-based innovation.
The crop of economic
writings that sprang from those few seeds constitutes an elaboration of three
core propositions which are fundamental to most of what contemporary analysts
have to say about the allocation of resources for basic scientific research. [6] First, the economic value of basic research is difficult to
forecast, or even to gauge in retrospect. Economic payoffs entrained by scientific
discoveries may come quickly, but more often are not realized for a long time. Since basic research occurs on the frontiers
of knowledge, its outcomes are highly uncertain. Second, realization of economic rents
(‘profits’) from a basic research advance also will be impeded to the degree to
which property rights in such discoveries are intrinsically difficult to
establish and defend, and because the organizational norms within which much of
such research is conducted (by academic scientists) inhibits effective
assertion of individual property rights that can readily be conveyed to other
parties, such as business corporations. From this it follows that the private returns
to investment in basic research are highly uncertain, especially in relation to
the benefits that will accrue to society as a whole. The economic payoff to society can be quite
large compared to the amount invested, because a fundamental advance in
knowledge can serve as an input for applied research and commercialization
efforts, leading to many new products and processes.
This divergence between the
private and social returns to basic research outlays has led to the third and
most influential proposition, namely, that there exists a systematic ‘market
failure’ which, in the absence of remedial actions, would result in societal
‘underinvestment’ in science. [7] The modest
share held by basic research within the R&D budgets of US corporations
(about 5% in 1985, for example) lends a good bit of credence to this
conclusion, even if it cannot indicate whether company financing of basic
science is below the level that would be socially optimal.
6. The summary statement given here draws on the exposition in David et
al. (1992)
490
Such qualifications have been left aside, and the
foregoing ‘market failure’ argument has stood as the central economic rationale
for the public funding of science for the past 30 years (see Mowery, 1983).
As impressive an
achievement as that may be in its practical consequences, what we may respectfully
refer to as ‘the old economics of science’ did not go much farther. Its approach to the production, dissemination
and uses of scientific knowledge was partial in nature, and therefore largely
incomplete in its ability to come to grips with most of the concrete issues in
the formulation and implementation of public policies affecting basic science. The literature in question began by treating
knowledge as a commodity, more specifically, as a durable public good. However, although the peculiarities of
information as a commodity were recognized from the outset, for the purpose of
analyzing the central issues of public finance posed by basic science,
economists began by treating knowledge entirely on a par with other forms of
durable public goods. Little effort was
directed to exploring the resource allocation implications of the respects in
which knowledge differs from other durable public goods, such as, for example,
laws and constitutions, or lighthouses, for that matter.
One consequence was that
the rules, regulations, and more generally ‘norms’ and ‘customs’ governing the
production of knowledge and its uses by members of the various research
communities, ranged under the headings of academic science, government science,
and industrial science, were taken as given by the older tradition - if,
indeed, they happened to be noticed explicitly. That these norms and characteristic
organizational forms are in fact sharply differentiated across these
communities of scientists, and quite unlike the background institutions
relevant in the case of other durable public goods, was not seen as something
of particular economic import, and therefore deserving of explanation. In the older tradition, neither the
historical origins nor the possible present raison d’etre
of these generalized ‘institutions’ are subjects of active inquiry among
economists or economic historians.
In a pair of joint articles
(Dasgupta and David, 1987, 1988) developed over the
past several years we have tried, by synthesizing insights from economics and
sociology, to carry the economics of science beyond the traditions of this
older literature. A first goal was to
provide an ‘explanation’ for the prevalence of distinctive norms, customs and
institutions governing university science, on the one hand, and industrial
R&D, on the other. [8] The phenomena
that interested us naturally included those salient social arrangements that
have occupied the attention of sociologists and philosophers of science: rules
of priority and the role of validated priority claims in the reward structure
of (academic) scientists, patenting and disclosure policies, and institutions
associated with scientific communication and the functioning of a collegiate reputational reward system - ranging from ‘invisible
colleges’ to organized, professional academies in various disciplines. This explanatory approach, however, departs
from that of the sociologists and philosophers.
A considerable part of the
characteristic style of analysis in the new economics of science derives from
its recognition of three features of the processes for the production,
dissemination, and use of knowledge. First
is the fact that certain crucial inputs, such as research effort, care, innate
scientific talent, and the realization of elements of chance in the process of
discovery, are very costly for outsiders to monitor, and in most cases are not
even observable jointly by the ‘principal’ who is sponsoring the inquiry (e.g.
a private or public patron or employer) and the principal’s ‘agent’ (the
researcher). Second is the observation
that there often are significant aspects of indivisibility, and attendant fixed
costs and ‘economies of scale’, inherent in the underlying processes of
knowledge production. Third is the point
that the knowledge generated in research activities, rather than being
inherently available to others, can be kept from the public
7. The existence of a positive gap between the social rate of return on
basic research outlays and the private rate of return on industrial capital
expenditures has been repeatedly confirmed empirically by sample calculations
that elaborate on the methodology of Griliches (1960)
- see Mansfield (1991) for recent examples; but the problems of the representativeness of the sample cases studied remain
formidable.
8. We associated university science with the world of ‘episteme’ and the
republic of science, whereas the latter we associated with the realm of
technology.
domain should the researcher so choose; the characteristics
of the reward system, along with the costs entailed, determines what
information gets disclosed fully, what is disclosed partially; and what is kept
secret. Given these structural
conditions, and the long-standing observation that the production of knowledge
is shot through with uncertainty, [9] it is quite in order to re-examine features of
organized research activities from the perspective offered by the recently
developed analysis of resource allocation under conditions of asymmetric
information.
As will be illustrated by
this paper, the new economics of science has the two-fold ambition of (1) exposing
the underlying logic of the salient institutions of science, and (2) examining
implications of those differentiating institutional features for the efficiency
of economic resource allocation within this particular sphere of human action. To carry out this program we will be building
upon the foundations laid down by the classic contributions in the sociology of
science, [10] adding to the insights provided by the ‘old’
economics of science some new ones that are drawn principally from the rapidly
growing analytical literature that treats problems of behavior under incomplete
and asymmetric information (including the economic theories of agency and
optimal contract, or ‘mechanism design’ theory), as well as issues in the
dynamics of racing and waiting games.
The remainder of this
article has the following organization. Section
3 defines some terms relating to the concepts of knowledge and information, and
introduces the generic problem of analyzing the relationship between market and
non-market ‘systems’ for governing the production and distribution of
knowledge. The logic of the reward
system in academic science, its relationship to the Mertonian
norm of ‘communality’ (complete free disclosure), and the central role played
by priority of discovery, are briefly considered in Section 4. Section 4 then goes on to sketch an economic
theory of departures from the norm of complete disclosure by treating as
endogenous the location of the boundary-line between knowledge that is codified
and that which is left tacit by scientists. The question of the efficiency of resource use
under the institutional constraints of a collegiate reputation-based reward
system funded by public patronage, such as exists in many Western nations, is
considered next. Sections 5 and 6,
respectively, focus on sources of misallocation within and between fields at a
given point in time, and in the timing of support provided for research
programs. It is shown that some of the
sources of these allocative inefficiencies lie close
to the institutional core of the system, so that the problems of correcting
them are by no means straightforward.
Although most of the
readily observed qualitative features familiar to sociologists of modern
science, working at both the macro-institutional and micro-behavioral levels,
can be accounted for by our analytical approach, it is symptomatic of the
relatively underdeveloped status of the new economics of science that many of
its implications remain unexplored and untested against systematic, quantitative
data. Furthermore, as is generally the
case when a new theoretical perspective is gained, new questions and puzzles
arise even as old ones are settled. The
agenda for future research in this field, therefore, remains both extensive and
varied. Nevertheless, even in its
present nascent state, the new economics of science can offer some measure of
guidance for science policy, suggesting points at which public interventions in
the resource allocation process are likely to be socially beneficial and others
where they are probably best avoided - leaving discretion to individual
scientists and scientific communities. Specific
implications bearing on issues noticed in the introduction are remarked upon
throughout the text and notes of Sections 3-6. Section 7 takes up a more extended analysis of
several interrelated policy issues raised by current moves to: (1) readjust the
balance of incentives influencing the production of Ph.D. scientists and
engineers and to alter the way trained researchers
9. For early efforts to quantify the uncertainty surrounding the
duration, costs, and success of industrial research projects, see Mocking
(1962) and Norris (1971). We are unaware
of comparable studies based on the experience of university scientific
researchers, but there is a presumption that, because the latter are less
constrained to select problems where the feasibility of a solution is less
clearly established, the research duration and costs associated with a
successful outcome typically are even more difficult to predict with accuracy.
10. For example, Merton (1973), Polanyi (1951, 1962, 1966), Hagstrom
(1965), Ziman (1968), Gaston (1970), Zuckerman and
Merton (1971, 1972), Ravetz (1971), Cole and Cole
(1973), Salomon (1973), Blume (1974), Mulkay (1979). Luhmann (1979), Nelkin (1987), Whitley (1984).
492
distribute themselves among entities engaged in open
science, mission-oriented government research, and proprietary R&D; (2)
encourage ‘transfers’ of academic research results to industry, by modifying
university regulations and contractual arrangements involving intellectual
property rights. The brief concluding
Section 8 therefore offers no more than a summary set of propositions to
underscore the general cautionary message emerging from the analysis: short-run
policies aiming to shift resources towards commercial applications of
scientific knowledge (by dismantling bits of the distinctive institutional
infrastructures of Science, or by weakening its ability to hold talented
researchers in the face of competition from business) may seriously jeopardize
a nation’s capacity to benefit, from a sustained flow of innovations based upon
advances in scientific and technological knowledge.
3. Knowledge: Codified or tacit?
Public or private?
As is the case in other specialized
fields of inquiry, in this one some specific terminological conventions will be
employed. A few initial definitions and
distinctions will avoid later confusions, especially since many of the terms we
employ are given somewhat different meanings in ordinary language usage and in
the scholarly literature on the intellectual and social organization of the
sciences.
3.1. Knowledge, information, and the endogeneity of tacitness
By the term ‘information’
(following common usage in economics) we will mean knowledge reduced and
converted into messages that can be easily communicated among decision agents;
messages have ‘information content’ when receipt of them causes some change of
state in the recipient, or action. [11] Transformation of knowledge into information is, therefore, a
necessary condition for the exchange of knowledge as a commodity. ‘Codification’ of knowledge is a step in the
process of reduction and conversion which renders the transmission,
verification, storage and reproduction of information all the less costly. [12] Yet, somewhat paradoxically, this
transformation makes knowledge at once more of what is described (in the public
finance literature) as a ‘non-rival’ good, that is, a good which is infinitely
expansible without loss of its intrinsic qualities, so that it can be possessed
and used jointly by as many as care to do so. [13] Thus, codified scientific knowledge possesses
the characteristics of a durable public good in that (i)
it does not lose validity due to use or the passage of time per se, (ii)
it can be enjoyed jointly, and (iii) costly measures must be taken to restrict
access to those who do not have a ‘right’ to use it. [14]
In contrast, tacit
knowledge, as conceptualized by Polanyi (1966),
refers to a fact of common perception that we all are often generally aware of
certain objects without being focused on them. [15] This does not make them less important: they form the context
which makes focused perception possible, understandable, and productive. No less than other human pursuits, science
draws crucially upon sets of skills and techniques - the
11. Shannon’s well-known measure of the quantity of information (see
Shannon and Weaver, (1949)) was formulated to serve the specific needs of
communications theory, and has been found unsuitable for application in
economics.
On this
see, e.g., Arrow (1964) and Marschak (1971).
12. This usage is related to, but does not carry the broader
implications of the concept of ‘codification’ in science as developed by
Zuckerman and Merton (1972): “The consolidation of empirical knowledge into
succinct and interdependent theoretical formulations.” According to the latter, scientific fields differ
in this regard, with those disciplines that remain in what Kuhn (1962) would
call a ‘pre-paradigm state’ being necessarily less ‘codified’.
13. Were person A to give person B a piece of information concerning Q,
that would not reduce the amount of information concerning Q that was retained
by A, (although, to be sure, the benefit to each would depend upon whether and
in what manner B were to make use of the information). Romer (1990, 1993)
has recently popularized this application of the term ‘non-rival’ good, but see
David (1993b) for the proposal of ‘infinite expansibility’ as an alternative
term that is less confusing, in that it acknowledges the possibility of
rivalries for possession of new information.
14. Even in the case of codified knowledge the condition of strict
non-excludability (namely, that once produced it is impossible to exclude
anyone from benefitting from it), which is taken to
be one of the hallmarks of a pure public good, does not hold; patents,
copyrights, and trade secrecy are institutional devices for denying others
beneficial access to information.
ingredients of ‘scientific expertise’ - that are acquired
experientially, and transferred by demonstration, by personal instruction and
by the provision of expert services (advice, consultations, and so forth),
rather than being reduced to conscious and codified methods and procedures. The transfer process itself, as a rule, is a
comparatively costly affair (in contrast to the case of codified knowledge) for
both the provider and the recipient of tacit knowledge, but, like information,
tacit knowledge can be swapped in transactions resembling ‘gift exchanges’, or
sold for money, rather than being shared freely. [16]
Insofar as codified and
tacit knowledge are substitutable inputs (at the margin) in the production of
further knowledge, or in practical implementations, the relative proportions in
which they are used is likely to reflect their relative access- and
transmission-costs to the users. Similarly,
differences in the extent to which knowledge generated by researchers in
various fields gets codified for packaging as information, rather than retained
in a tacit form, will reflect the reward structures within which researchers
are working, as well as the costs of codification. Hence, variations in the
relative importance of codified and tacit knowledge in the work of different
research communities has no necessary connection with the ‘hardness’ or
‘softness’ of their respective disciplines. This perspective, afforded by the new
economics of science, stands in contrast with the disposition of some
philosophers and historians of science to associate a relatively high degree of
codification with occupancy by the discipline in question of a superior
position in some epistemological or methodological hierarchy. [17] Some recent discussions of the economics of
R&D and technology transfers (e.g. Pavitt, 1987;
Nelson, 1990; Rosenberg, 1990) continue to assign special significance to the
tacit elements in technological knowledge, calling attention to the fact that
the information contained in patents, blueprints and other codified forms of
knowledge often are insufficient for successful implementation of the technical
innovations they purport to describe; much complementary ‘know-how’ may be
required, the acquisition of which, typically, is a costly business. While we regard the factual proposition to be
beyond dispute, to our way of thinking its does not imply the existence of
underlying, intrinsic differences in the nature of ‘technological’ as opposed
to ‘scientific’ knowledge. [18] Certainly, we would dispute the assertion that technological
knowledge, on that account, should be assigned a subordinate epistemological
status. Furthermore, we find no compelling
grounds for associating the tacit knowledge of either technologists or
scientists necessarily with skills that are specific rather than ‘generic’ in
their applicability. [19] Going back to Polanyi’s
perceptual analogy, what gets brought into focus (and codified) and what
remains in the back-
15. Whereas philosophers of science (e.g. Nagel, 1961; Hempel, 1966; Popper, 1968) emphasized the epistemological
bases for distinguishing between the scientific and other modes of human
understanding, stressing formal methodological rules of ‘scientific procedure’,
Polanyi’s (1966) insights concerning the ubiquitous
role of tacit knowledge has led some modern sociologists of science (e.g. Latour and Woolgar, 1979; Latour, 1987) to study the practice of laboratory science
as a ‘craft’.
16. See Hagstrom (1965) on gift exchanges
among scientists, and Arora (1991) on contractual
arrangements for the sale of tacit information by business firms.
17. See, for example, Kuhn (1962), and also Nagel (1961), Hempel (1966), and Popper (1968), who suggest that it is
the role played by formal methodological rules of ‘scientific procedure’ that
provides epistemological grounds for distinguishing between (hard) science and
other (softer) modes of human understanding.
18. This challenges Vincenti’s (1990a, p. 19)
characterization of his writings as having shown that “engineering knowledge
warrants recognition as an epistemological species in its own right”. In actuality, however, it is primarily on
sociological and behavioral, rather than epistemological, grounds that Vincenti (1990a,b) shows
engineering and science to be different pursuits. He says knowledge is an instrumentality in
both, whereas they give priority to different ends: scientists to understanding
of ‘how things are’, and engineers to ‘how things ought to be’, i.e. with
solving practical problems. Even
supposing that was so, it would not logically imply a difference in the nature
of the means (knowledge) employed, or in their reliability. Furthermore, Vincenti’s
differentiation on grounds of proximate goals rather closely resembles our view
of Science as a sphere of activity whose organization is conducive to the rapid
growth of the stock of knowledge, whereas Technology is concerned to achieve
rapid growth of the material benefits from new knowledge.
19. Nelson (1990) makes the same point, but associates what he refers to
as the ‘generic’ parts of technological information with codified knowledge
that can be readily transferred, and which tends therefore to become public,
whereas he identifies the tacit knowledge components with ‘specific’
technological information that is privately held.
494
ground (as tacit knowledge) will be, for us, something to be
explained endogeneously by reference to the
structure(s) of pecuniary and non-pecuniary rewards .and costs facing the
agents involved. Although the position
of the boundary between the codified information and tacit knowledge in a
specific field of scientific research may be shifted endogenously by economic
considerations, the complementarity between the two
forms of knowledge has important implications for the way research findings can
be disseminated. We comment on these
below (in Section 7.3, especially) in connection with recent discussions of
measures to promote the transfer of university research results to industry for
further development and commercial exploitation.
3.2. Science and Technology: Public and private
knowledge
Although the foregoing
discussion has referred to scientists and technologists in ways that suggest
they are different kinds of knowledge-workers, the crucial distinction we seek
to draw is between the social organizations of Science and Technology. By capitalizing the terms we signify that
these labels are being used here to refer to the two sets of socio-political
arrangements and their respective reward mechanisms affecting the allocation of
resources for scientific research. For
our purposes, what fundamentally distinguishes the two
communities of researchers is not their methods of inquiry, nor the nature of
the knowledge obtained, nor the sources of their financial support. To be sure, differentiations between can be
drawn along those lines, as already noted, but to our way of thinking much of
the economics literature, like philosophy of science, has mistakenly focused
upon science-technology distinctions that are epiphenomena of differences that
lie at a deeper level. It is the nature
of the goals accepted as legitimate within the two communities of researchers,
the norms of behavior especially in regard to the disclosure of knowledge, and
the features of the reward systems that constitute the fundamental structural
differences between the pursuit of knowledge undertaken in the realm of
Technology and the conduct of essentially the same inquiries under the auspices
of the Republic of Science.
Loosely speaking, we
associate the latter with the world of academic science, whereas Technology
refers to the world of industrial and military research and development
activities. What makes a
knowledge-worker a ‘technologist’ rather than a ‘scientist’, in this usage, is
not the particular cognitive skills or the content of his or her expertise. The same individual, we suppose, can be
either, or both, within the course of a day. What matters is the
socio-economic rule structures under which the research takes place, and, most
importantly, what the researchers do with their findings: research undertaken
with the intention of selling the fruits into secrecy belongs unambiguously to
the realm of Technology. Secrecy,
however, is more readily effected when knowledge is not codified in proprietary
documents (e.g. blueprints, receipts for chemical syntheses) that can be
purloined and published, but instead is retained in a tacit form. Training services that convey tacit
information and .access to contracting with the trained are commodities that
can be, and are, exchanged for value by business organizations operating within
the realm of Technology, and also by academic research organizations, although
the enforceability of contracts tends to differ between the two cases, and the
terms on which tacit information can be sold are correspondingly different. [20] None of this implies that profit-seeking business firms
would not find it to their advantage on occasion to invest some resources in
‘basic’ research, or organize research facilities in ways that emulated the open,
cooperative environment characteristic of university campuses. Neither does it imply that academic scientists
will never seek to benefit materially by patenting their inventions, or always
refrain from rivalrously withholding research
findings and
20. Of course, as we have acknowledged in the text above, epistemological
and methodological differences exist between the two research communities. For example, it is widely believed that among
applied industrial scientists, engineers, and like technologists the balance
between codified and tacit knowledge (‘practical know how’) tilts more towards
the latter than is the case among university researchers. Yet as we already have suggested, such a
difference could well be a consequence of the different information disclosure
rules and reward systems that obtain.
methods from university-based researchers in their field. [21]
It is equally possible to arrive
at the foregoing, highly stylized view of the scientific research world via
another route, namely, by starting from a consideration of the main alternative
resource allocation mechanisms that can be used to produce and distribute
scientific knowledge, and considering the efficiency with which they will
perform those tasks. Of all possible
resource allocation mechanisms, the one that has been most studied in economics
is the ‘market mechanism’. As is now
well known, if the market mechanism is not aided by further social
contrivances, such as, for example, intellectual property rights, there is no
basis for supposing it can sustain an efficient production of knowledge. The market mechanism has a tendency to
discourage the production of public goods because of an inability on the part
of producers to appropriate fully the value of the fruits of their efforts. [22] Three generic remedies have been devised to overcome the
deficiency of the market in this regard: two of them do so by seeking to
rectify the problem at its source, whereas the third solution applies
correctives in the form of supplements to the market outcomes. Let us briefly look at each of these schemes
in turn.
(1) The first scheme
consists of the government engaging itself directly in the production of
knowledge, allowing free use of it, and financing the production cost from
general taxation. This was at the heart
of Samuelson’s (1954) analysis of the efficient production of public goods. Government research and
development (R&D) laboratories that publicly disclose their findings, such
as agricultural research establishments, - are an ex ample of this. It is as well to note that under this scheme
the volume of public expenditure in the production of knowledge, and the
allocation of expenditure for the production of different kinds of knowledge,
are both public decisions: they are decisions made by the government.
(2) A second possible
solution is for society to grant intellectual property rights to private
producers for their discoveries, and permit them to charge (possibly
differential) fees for their use by others. This creates private markets for knowledge. Patents and copyrights are means of defining
and protecting intellectual property rights, and as their strengths and
weaknesses have been discussed extensively by economists over the years, we
shall not embark upon that subject here. [23] It should be observed, nonetheless, that the producer (or owner) of a
piece of information in this scheme, ideally, should set different prices for
different buyers, because different buyers typically value the information
differently. [24] One problem with such markets is that they are inevitably
‘thin’ (each market is essentially a bilateral monopoly, i.e. consisting of the
seller and a single buyer), and therefore not a propitious environment for the
emergence of prices that will sustain an efficient allocation of resources, as
has been pointed out by Arrow (1971). Another
problem with them arises from the fact that transactions in knowledge are shot
through with leakage. The point is that
for an exchange to be conducted efficiently, both parties need to know the
characteristics of the commodity being transacted. In our example, the potential buyer needs to
know what the piece of information is before the transaction is concluded, but
once the potential buyer gets to know the information, it is difficult for the
seller (e.g. the inventor-developer) to prevent the prospective buyer from benefitting from what she has learned, should
the contemplated transaction not be concluded. [25] This feature of knowledge
21. It is the identification of Weberian
‘ideal types’ that endows the instances of deviance with interest and potential
significance, as will be seen below in Section 4.2, for example.
22. This is the well-known ‘free rider’ problem in the supply of public
goods. The earliest writers on this were
Knut Wicksell and Eric Lindahi. See
Musgrave and Peacock (1958) for abridged versions of the Wicksell-Lindahl
analyses. Modern statements of the
allocation problem associated with public goods are in Samuelson (1954) and
Arrow (1971). The basic economics of
public goods can be found in any textbook on public finance (e.g. Musgrave,
1968; Stiglitz, 1988.)
23. See for example, David (1993a,b) for
citations to and discussion of recent contributions to the economics literature
on intellectual property rights.
24. In economics, these variegated prices are called Lindahl
prices, in honour of Eric Lindahl,
who first articulated a scheme of this kind, (see Musgrave and Peacock, 1958).
25. Arrow (1962) argued that this is a particular difficulty whenever
the transaction involves the fruits of fundamental research, for the findings
of such research have possible applications in wide varieties of fields, some
of which are not known to the would-be seller.
496
(that its value is often very
difficult to quantify) will figure prominently in what follows. It means that the economic use-benefits of
knowledge are often hard to appropriate privately, and
therefore to market efficiently. This is
so even when patent protection of knowledge gives the owner transferable legal
rights to exclude others from using that knowledge in many specified contexts. [26]
The foregoing tells us that
despite the limitations of the institutions of patents and copyrights (and, for
that matter, the legal protections for secrecy among individuals and
organizations), those ‘property-like’ contrivances
provide means for privately appropriating profits from discoveries and
inventions. In short, while information can
in principle be used jointly, joint use can be prevented by legal prohibitions
or through the practice of secrecy. This
can be socially desirable, because even though monopoly in the use of knowledge
is inefficient (it involves the under-utilization of knowledge), it can be
offset by the act that the lure of monopoly profits makes researchers undertake
R & D activity today. Therein lies the value of instituting patent laws, and of allowing secrecy
to be practised by discoverers.
(3) A third possible scheme
is for society to encourage private production of knowledge by offering public
subsidies for its production, and by relying upon general taxation to finance
these subsidies. A critical feature of
this arrangement is that producers are denied exclusive rights to the output of
their R&D activity: once it is produced, the knowledge is made freely
available to all who care to use it. [27] In albeit
imperfect forms, this scheme characterizes research activities carried on in
public and private non-profit entities, such as universities, where much of the
knowledge that is produced is prohibited from being patented by the private
individuals involved in creating it, and where salaries, promotions and
equipment are paid out of public funds (the subsidies!). We will study this resource allocation
mechanism further in Section 4, where we will examine the role assumed -by a
special form of intellectual ‘asset’, namely an accepted claim to priority of
discovery or invention which, though not a legally recognized property right,
nonetheless plays a crucial role in making the scheme more effective than it
would otherwise be.
While the public finance
literature provides some guidance to the problem of providing for the
production of scientific knowledge, it does not take us very far. There are many, points where the standard
prescription of subsidies remains unsatisfyingly
vague. Should the subsidy be based on
scientists’ research time? Or should it
be adjusted according to the nature of their endeavors? Or should it instead be granted on a
piece-rate basis for ‘output performance’ measured in some convenient way -
such as publications in scientific journals, or the frequency with which their
(codified) findings are cited in other scientific publications, and in patents?
As it happens, this vagueness reflects a
deeper weakness. The literature leaves
unexplored the intricate institutional structure governing the practice of
science. Nor does it build on the fact
that research activity not only involves considerable uncertainties, but is
shot through with choices the consequences of which are publicly unobservable. Without an understanding of these features of
scientific activity, it is not possible to devise efficient subsidy schemes. Recent explorations in the economics of
science focus their attention on these matters. We turn to them now.
It will be noticed from
even the preceding sketch that the first and third resource allocation mechanisms
in our list are similar in an important way: the output of research is publicly
shared. In contrast, the second
mechanism treats output as a private good. To be sure, the second scheme differs from the
other two also as regards the source of funds: private versus public. But we maintain that to emphasize differences
in the sources of funding is not a particularly illuminating way of
distinguishing Science from Technology. Government
laboratories engaged in military research are publicly funded, but the secrecy
that
26. Matters are easier in the case of narrowly restricted knowledge
about new technical processes and practical devices. This partly explains why it is a commonplace
today to see A paying B a license fee for using B’s
patent on the manufacture of a new product, or on a new process for
manufacturing an old product.
27. See Pigou (1932), Baumol
and Oates (1975) and Dasgupta and Heal (1979).
is maintained over their findings makes them part of
Technology. [28]
So, for the purposes of the
present discussion we can amalgamate the first and third schemes into one - on
the grounds that their attitudes towards controlling the output of research are
similar. Having thereby reduced the
distinctive modes of organization from three or two, one may still ask: Is this
still not one more than is really needed? The question can be answered in the negative,
on the functionalist grounds that they are adapted to serving distinctive
goals: the community of Science is concerned with additions to the stock of
public knowledge, whereas the community of Technology is concerned with adding
to the stream of rents, that may be derived from possession of (rights to use)
private knowledge. [29] The arrangements within each can be
shown to have an internal coherence and logic which, while not perfectly
efficient, is quite well-suited to serve its (imputed) purpose. [30] Thus, because their functional attributes are
not the same, there is no cause for thinking it is paradoxical for a given
society simultaneously to organize scientific inquiries in two quite
distinctive modes, maintaining the two sets of institutional mechanisms and
behavioral norms characteristic of the research communities we have delineated.
Although it is evident from the
contradictory norms on which they are based that there is a tension between
these two modes of economic and social organization, so that they do not ‘mix’
easily, the two are not mutually exclusive ways to successfully organize the
pursuit of scientific knowledge within the same society. Indeed, we will argue that in order to ensure
a reasonably efficient allocation of resources in the production of knowledge,
modern societies need to have both communities firmly in place, and attend to
maintaining a synergetic equilibrium between them.