2. 468 BULLETIN OF SCIENCE, TECHNOLOGY & SOCIETY / December 2007
or typology of innovation policies (Alic, 2002; Alic, conceive innovation as a complex process involving
Mowery, & Rubin, 2003; den Hertog & de Groot, 2005) different actors and their interactions.
and a scarcity at the EU level (Kuhlmann, 2002; Systems strive to achieve goals for which their ele-
Lundvall & Borrás, 2005; Rothwell & Dodgson, 1992; ments fulfill specific functions. Different typologies of
Smits & Kuhlmann, 2002). system functions have been developed with different
Although many types of policies affect innovation, no degrees of detail and emphasis (Johnson, 2001). A gen-
universally accepted criteria classify them. Taxonomy or eral typology of innovation system functions set out
typology of innovation policies seldom includes regu- three categories, namely, reduction of uncertainty, man-
latory policies, such as environmental or competition agement of conflict and cooperation, and provision of
regulation. Regulatory policies can strongly influence incentives (Edquist & Johnson, 1997).
innovation. The environmental literature (e.g., Blind et al., Once the model is chosen, innovation policies can be
2004; Jaffe, Newell, & Stavins, 2003; SQW, 2006) devised. Although there is a lack of consensus on the
includes many studies of regulation-induced innovation, definition of public policy, Birkland (2001) indicates
such as the development of greenhouse gas emission elements common to all definitions of public policy:
controls. Likewise, energy policy also has affected inno- The policy is made in the name of the “public”; policy
vation. For example, efficiency standards have reduced is generally made or initiated by government; policy is
the average energy consumption of household appli- interpreted and implemented by public and private
ances (e.g., Rubin, 2001). In addition, competition policy actors; policy is what the government intends to do.
is recognized as shaping innovation (e.g., Hart, 2001). Regarding the theoretical framework of policy instru-
All in all, this study focuses on taxonomic and typo- ments, Lascoumes and Le Gales (2007) present two
logical methods of innovation policies in the institutional arguments. Firstly, public policy instrumentation is a
context of the EU. The article is organized as follows. To major issue in public policy, as it reveals a theorization
begin with, innovation per se, models of innovation, and of the relationship between the governing and the gov-
innovation policy are discussed. In Section 3, the EU pol- erned: Every instrument constitutes a condensed form of
icy and regulation process are briefly described. In knowledge about social control and ways of exercising
Section 4, data and methodology used for the taxonomy it. Secondly, instruments are not neutral devices: They
and typology of innovation policy are specified. In produce specific effects, independently of the objective
Section 5, the resulting taxa and types of the EU policies pursued (the aims ascribed to them), which structure
on innovation are shown. In Section 6, models on inno- public policy according to their own logic.
vation policies are depicted. Before concluding, science, Public policy instrumentation means the set of prob-
technology, and innovation policies are examined. lems posed by the choice and use of instruments (tech-
Finally, some concluding remarks are given. niques, methods of operation, devices) that allow
government policy to be made material and operational.
Theoretical Framework Another way of formulating the issue is to say that it
involves not only understanding the reasons that drive
In this section, we define the constructs needed for a towards retaining one instrument rather than another but
taxonomy and typology and thereby the scope for this also envisaging the effects produced by these choices.
study. At the outset, innovation is the successful produc- By way of indication, a brief catalogue of these instru-
tion, assimilation, and exploitation of novelty in the ments can be drawn up: legislative and regulatory,
economic and social spheres. In a more detailed way, economic and fiscal, agreement- and incentive-based,
innovation is the renewal and enlargement of the range of information- and communication-based. But observa-
products and services and the associated markets; the tion shows that it is exceptional for a policy, or even a
establishment of new methods of production, supply, and program for action within a policy, to be monoinstru-
distribution; and the introduction of changes in manage- mental. Most often, the literature notes a plurality of
ment, work organization, and the working conditions and instruments being mobilized and then raises the ques-
skills of the workforce (European Commission, 1995). tion of coordinating them (Bernelmans-Videc, Rist, &
Regarding innovation theories, the linear models Vedung, 1998).
study innovation as a process divided into different Apart from national governments, nongovernmental
stages (Rogers, 1995). In contrast, systemic models organizations, public-private partnerships, subnational
(Edquist, 1997, 2001; Edquist & Johnson, 1997; agencies, and supranational programs all promote inno-
Lundvall, 1992; Lundvall et al., 2002; Nelson, 1993) vation policies as well. In this study, we only focus on
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3. Rodriguez, Montalvo / INNOVATION POLICIES 469
the EU innovation policies. Institutionally, innovation
policies at the EU level must follow the principles of
subsidiarity and European added value. The first rule
means that those policies have to be justified through
supranational formulation that would not be effectively
managed by the member states, while the second princi-
ple requires from such policies a synergy effect not
attainable within the national borders.
The European Council (2000) in Lisbon applied the
open method of coordination (OMC) to innovation poli-
cies, introduced in the Employment Strategy of the
Amsterdam Treaty. The European Convention (2002)
decided not to codify the OMC within the European Figure 1. Early Stage of the Codecision Procedure
Constitution but recognized the special logic of innova-
tion policies by drafting a separate subarticle (Kaiser &
Prange, 2004).
Innovation policies in the EU are multifaceted, procedures that define how the EU will fulfill the goals
ingrained, and wide ranging, including all initiatives defined in the policies. They also may clarify policies or
regarding science, education, research, technology state law. The EU governance relies on the method that
development, and industrial modernization, overlapping arbitrates between different interests by two filters,
also with industrial, environmental, labor, and social namely, the general interest at the level of the
policies (Shapira & Klein, 2001). In fact, due to the Commission and democratic representation at the level
complexity of the innovation policy system at the EU of the Council and the Parliament. Innovation policies
level, a need of a typology arises. The epistemic strategy fall into the scope of the codecision procedure.
is to categorize EU innovation policies in line with two The Commission alone proposes policies and reg-
perspectives: biological and neofunctionalist. ulations. Besides that, the Commission has the ability
First, we use biological heuristics, a method by to execute policy. Regulatory and budgetary acts are
which species of organisms are classified, because we adopted by the Council, representing the member
consider the criteria useful for the purpose of our study. states, and the Parliament, representing citizens
Modern classification in biology has its root in the work (European Commission, 2001). Central to the EU’s
of Linnaeus, who grouped species according to shared decision-making system is the codecision procedure.
physical characteristics. These groupings have since This sets the principle of parity and means where nei-
been revised by molecular systematics, which uses ther the Parliament nor the Council may adopt legis-
DNA sequences as data (Simpson, 2006). lation without the other’s assent.
Second, from a neofunctionalist standpoint, European The Commission has a monopoly of legislative initia-
integration has brought a multilayered division of tive in all the areas that are subject to the codecision pro-
labor to classical nation-state functions. In these circum- cedure. Innovation is among them. The Commission’s
stances, innovation systems are stirred up by the increas- proposal is the result of an extensive consultation process
ing socioeconomic and political Europeanization since (see Figure 1), which may be conducted in various ways,
the 1980s. Nonetheless, EU innovation policies are still namely, impact assessment, reports by technical or scien-
pursued in parallel on the supranational, national, and tific experts, consultation of national experts, interna-
subnational levels. The justification for multiple but sep- tional organizations or nongovernmental organizations,
arate innovation policies at the EU level has been over- consultation via green and white papers, and so on. The
taken by changed circumstances (Georghiou, 2001). work of European contract research organizations such as
TNO, Fraunhofer ISI, or VTT plays a role in this phase.
EU Policies and Regulations A consultation process is also launched among the
different Commission departments in order to ensure that
In this section, we concisely depict the EU architec- all aspects of the matter in question are taken into
ture for producing policies and regulations. Under the account (interservice consultation). The Commission’s
EU governance system, policies are defined as expected proposal is adopted by the College of Commissioners on
outcomes of the EU work and provide a framework the basis of either a written procedure (no discussion
within which the EU operates. Regulations are the among Commissioners) or an oral procedure (the dossier
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4. 470 BULLETIN OF SCIENCE, TECHNOLOGY & SOCIETY / December 2007
Table 1. Frequency Distribution of EU Documents on
Innovation
2006
Year Council Parliament Commission
2000 21 25 52 2005
2001 10 55 68
2002 29 43 99 2004
2003 42 49 88
Year
2004 19 17 87
2003
2005 23 16 113
2006 51 41 106
Total 195 246 613 2002
Note: EU = European Union. Noise was only removed for 2006.
2001
2000
is discussed by the College of Commissioners) and is
published in the Official Journal of the European Union. 0 20 40 60 80 100 120
Documents
Then, the proposal is forwarded to the European
Parliament and to the Council simultaneously. Commission Parliament C ouncil
The Economic and Social Committee, representing
civil society, and the Committee of the Regions, repre- Figure 2. Chart of EU Documents on Innovation
senting local authorities, must be consulted by the Note: EU = European Union.
Commission and can be consulted by the Council and the
Parliament. Thenceforth, the Economic and Social taxonomy refers to a classification system that leads to
Committee and the Committee of the Regions may issue categorizing innovation policies into mutually exclusive
opinions in cases considered by them to be appropriate. and exhaustive sets with a series of discrete decision
After that, the codecision procedure takes place only rules, while a typological heuristic makes possible iden-
between the Parliament, Council, and Commission. tifying multiple ideal types, each representing indepen-
dent variables of the outcome. In our study, the outcome
Data and Method could be represented by the Lisbon goals, that is, to make
the EU the most competitive and dynamic knowledge-
As we aim to classify EU innovation policies, we based economy, capable of sustainable economic growth
assumed that those policies are embedded in documents. with more and better jobs and greater social cohesion.
For that reason, we resorted to documents published in A catalogue of all aspects and instances of EU pol-
Eur-lex. This reference center provides online access to icy innovation would obviously be quite unmanage-
the EU official journal, treaties, legislation in force, able. It would merely demonstrate that innovation
preparatory acts, case law, and parliamentary questions. policies are too diverse, too protean, to be captured in
The yearly frequency distribution of EU documents full by a single categorization. For that reason, two
on innovation from 2000 to 2006 is shown in Table 1 and strategies were designed to fully tackle the classifica-
Figure 2. Firstly, the analysis was restricted to documents tion problem of EU innovation policies.
containing the term innovation either in the title or in the The first strategy was to adopt two biological
text. Secondly, the working database was constructed by approaches to the problem of classification of EU
retrieving documents published in English by the innovation policies into a typology in order to provide
Council, the Parliament, and the Commission in the EU an epistemic horizon for cognitive purposes. Firstly, a
official journal. Thirdly, we chose only the year 2006 for Linnaean heuristic allowed us to classify EU innova-
illustrating typology of EU innovation policies. Finally, tion policies into a hierarchy that starts with domains
for 2006, we discarded those documents that contained and finishes with species. Secondly, a cladistic
the term innovation because they were not fully in line approach permitted us to arrange innovation policies
with our selected definition of innovation. In other only into their order of branching in an evolutionary
words, we removed noise only between January 1, 2006, tree (Luria, Gould, & Singer, 1981).
and December 31, 2006. In both cases, the underlying logic for each criterion
The semantic confusion of the terms taxonomy and is Aristotelian: Superior taxa possess similarities that are
typology is clarified by Doty and Glick (1994). The term common to all lower taxa, and lower taxa possess more
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5. Rodriguez, Montalvo / INNOVATION POLICIES 471
Table 2. Public Policy Instruments for Research and Development
Instruments in a Narrow Sense Instruments in a Broader Sense
1. Institutional funding 4. Public demand and procurement
National research centers
Research councils
Applied research and technology development organizations
Universities and other higher education institutions
Others
2. Financial incentives 5. Corporatist measures
Indirect promotion programs Long-term visions; technology foresight
Technology promotion programs Technology assessment
Risk capital Awareness initiatives
3. Other innovation infrastructure and technology transfer mechanisms 6. (Continuing) education; training
Information and consultancy for small- and medium-sized enterprises
Demonstration centers 7. Public policy
Technology centers Competition policy
Cooperation, networks, people Public stimulation of private demand
Source: Meyer-Krahmer and Kuntze (1992).
specificity that could make a difference from other taxa be budgetary decisions on allocating funds to public
at the same level of classification. For example, domes- research organizations, such as universities, and subsi-
tic policy is the counterpart of external policy and it con- dies or tax relief to private firms. The instruments used
sists of all government policy decisions, programs, and in technology policy may be public procurement and
actions that primarily deal with internal matters, as direct incentives in the form of subsidies and tax reduc-
opposed to relations with other countries that are not EU tions, supporting research at universities, finding institu-
member states. Major areas of domestic policy include tional mechanisms that link universities and public
economic policy and regulatory policy. Economic policy laboratories to the users of research, and designing and
refers to the actions that cover interest rates, governmen- enforcing intellectual property rights. The instruments
tal deficit, and labor markets, among others. Regulatory used in innovation policy pay special attention to the
policy refers to the implementation of rules to influence institutional dimension including competence building
the behavior of actors in society. and organizational performance, such as improving
The second strategy was to use a neofunctionalist individual skills and learning abilities.
heuristic for our typological approach. The ideal types Another way of constructing a technology policy
are complex constructs that must be described in terms typology could be in the manner of Alic and colleagues
of multiple dimensions and are not categories. Instead, (2003), who schematized the policy tools according to
each ideal type represents a unique combination of the (a) direct government funding of R&D; (b) direct or indi-
dimensions used to describe EU innovation policies. rect support for commercialization and production; (c)
Public policy instrumentation and its choice of tools indirect support for development; and (d) support for
and modes of operation are generally treated either as a learning and diffusion (see Table 3).
kind of evidence (e.g., governing means making regula-
tions, taxing, entering into contracts, communicating, Taxonomy and Typology of EU
etc.) or as if the questions it raises (the properties of Innovation Policies
instruments, justifications for choosing them, their
applicability, etc.) are part of a rationality of methods. A The old linear model of innovation embedded the first
good deal of the public administration literature devoted generation of innovation policy. The second generation
to the issue of instrumentation is marked by a function- of innovation policy was launched in the EU in 1995.
alist orientation (Lascoumes & Le Gales, 2007). Since the 2000s, the EU innovation policies belong to the
In particular, Meyer-Krahmer and Kuntze (1992) third generation, which implies having innovation at the
have defined research and development (R&D) instru- center of all policies in the knowledge-based economy
ments both in a narrow sense and in a broader sense (see according to the Lisbon strategy. For that reason, inno-
Table 2). The instruments used for science policy may vation goals can be found in a wide range of policies and
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6. 472 BULLETIN OF SCIENCE, TECHNOLOGY & SOCIETY / December 2007
Table 3. Technology Policy Tools
Direct or Indirect Support for
Direct Government Funding Commercialization and Production; Support for Learning and Diffusion of
of R&D Indirect Support for Development Knowledge and Technology
R&D contracts with private firms Patent prosecution Education and training (technicians, engineers, and
(fully funded or cost-shared) R&D tax credits scientists; business decision makers; consumers)
R&D contracts and grants with Tax credits or production subsidies for Codification and diffusion of technical knowledge
universities firms bringing new technologies to (screening, interpretation, and validation of
Intramural R&D conducted in market R&D results; support for databases)
government laboratories Tax credits or rebates for purchasers of Technical standard setting to ensure commonality
R&D contracts with industry-led new technologies or compatibility
consortia or collaborations Government procurement Technology and industrial extension services
among two or more actors above Demonstration projects Publicity, persuasion, and consumer information
(including awards, media campaigns, etc.)
Source: Alic, Mowery, and Rubin (2003).
Note: R&D = research and development.
Table 4. Linnaean Taxonomy
Domain Kingdom Division Class Order Family Genus Species
domestic economic industrial entrepreneurial innovation technology biotechnology policy, genomics policy,
policy policy policy policy policy policy information database
technology policy, etc. policy, etc.
domestic economic industrial entrepreneurial innovation nontechnology organizational training and
policy policy policy policy policy policy policy education
policy
domestic regulatory fiscal tax income tax corporate incentive tax deduction
policy policy policy policy policy policy policy policy
regulations. Innovation could be directly or indirectly More specific sectoral polices may deal with biotech-
addressed by the policies and regulations. In this section, nology or information technology policy. Among these,
the results of our typology are displayed. genomics and database policies can be found. Non-
The Linnaean heuristic exemplified to some extent in technological aspects of innovation, such as provision of
Table 4 shows a degree of specificity of innovation poli- training and education as sources of innovation, can show
cies. To begin with, domestic policy is the complement another type of species of EU innovation policy.
of foreign policy and it primarily deals with internal mat- Regarding regulatory policies, tax deductions are an
ters, as opposed to relations with other countries that are example of this criterion.
not EU member states. Examples of the second are poli- The cladistic approach here simply arranges
cies to foster innovation in neighboring countries, evalu- the innovation policies in an evolutionary tree. For
ation of innovation policies of accession countries, and instance, domestic policy in the cladogram (see Figure 3)
improvement of innovation in third countries. shows that technological and nontechnological poli-
Major areas of domestic policy include economic pol- cies stem from innovation policy and this comes
icy and regulatory policy. For instance, the promotion of from entrepreneurial policy that derives from indus-
innovation for the knowledge-based economy illustrates trial policy in economic policy. As it was already
economic policies dealing with innovation. One example said, the first strategy was to adopt the two biologi-
of industrial policy for innovation is the encouragement cal approaches in order to provide a frame for epis-
of innovation in the food sector. One example of entre- temic rationale.
preneurial policy is the state aid for small- and medium- The second strategy used a neofunctionalist heuristic
sized enterprises (SMEs). One example of innovation for our typology. Thus, the following first-order con-
policy is the innovation policy tools. Examples of tech- structs were formulated for this attempt: (a) content, (b)
nology policy are those that promote innovation in media, axis, (c) time horizon, (d) process, (e) action, (f) goals,
agriculture, health, food, fisheries, and nuclear sectors. and (g) division of labor.
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7. Rodriguez, Montalvo / INNOVATION POLICIES 473
EU innovation policy management
EU innovation policy management
Figure 3. Cladogram
0 20 40 60 80
Frequency of documents on EU innovation
State aid to SMEs Finance and budget
Firstly, innovation policies content is a criterion Innovation policy tools Policy coherence
because innovation is pervasive; many policy areas
have an impact on innovation. Among the subject mat- Figure 4. European Union (EU) Innovation Policy Management
ter of these documents, innovation appeared in texts Note: SMEs = small- and medium-sized enterprises.
related to agriculture, competition, culture, democ-
racy, development, economy, education, employment,
energy, environment, EU accession, EU neighbor- Fifthly, as far as the action involved with innova-
hood, external relations, finance, fishery, food, health, tion policies, innovation policies can cover their
human rights, information and communication tech- design, implementation, management, and assess-
nologies, manufacturing, intellectual property rights, ment. Regarding the design of instruments, the
media, networks, policy coherence, regions, science, Commission’s proposal is the result of an extensive con-
security, social aspects, standardization, trade, trans- sultation process. Those consultative documents can be
port, and youth. blue books, white papers, green papers, and reports. A
Secondly, with respect to axis, innovation policies blue book is a book of specialized information. A white
can be vertical or horizontal. Vertical policies, very paper is a detailed or authoritative report. A green paper
important for implementation, depict relationships is a document that proposes and invites discussion on
between different institutional layers. For instance, approaches to a problem. A consultative report can be
sectoral policies for innovation depict vertical poli- produced by technical experts, national experts, interna-
cies, namely, improving innovation in the media and tional organizations, or nongovernmental organizations.
audiovisual sector, agriculture, health, food, transport, Regarding implementation, innovation policies can also
fisheries, and nuclear sectors. Horizontal policies are be embodied in frameworks, actions, implementation
essential for coordination of many policy domains to plans, or programs. Innovation policies appear in other
achieve better innovation policy in a multisectoral policy declarations. Regarding management, innovation
approach, such as promoting innovation for a knowledge- policies can be embodied in state aid to SMEs, finance
based economy. and budget, policy coherence, and other innovation pol-
Thirdly, with regard to time horizon, innovation icy tools (see Figure 4). Finally, the assessment of inno-
policies could be characterized as short-, medium-, or vation policies can be embodied in reports produced by
long-term. One example of the first is state aid to impartial experts.
SMEs. One example of the second is finance and bud- Sixthly, innovation policies can have direct or indi-
get. One example of the third is the fulfillment of rect goals. In 2006, documents dealing with innova-
researchers’ scarcity. tion policy design in a direct way contained sectoral,
Fourthly, concerning policy process, innovation regional, external, labor, and macroeconomic aspects
policies can be made collectively or institutionally (see Figure 5). The documents that dealt with innova-
(March & Olsen, 1996). Collective policy making is tion policy indirectly addressed topics other than
seen as bargaining behavior and policy as negotiated innovation such as education, environment, culture,
outcomes, such as developing innovation in regions. standardization, and so on (see Figure 6).
Institutional policy making implies matching institu- Finally, policies can be classified by the governmental
tions, behaviors, and contexts, such as maintenance of actors responsible for their design and implementation.
innovation in the nuclear sector. In science policy, the main policy actors are those
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8. 474 BULLETIN OF SCIENCE, TECHNOLOGY & SOCIETY / December 2007
Improve innovation in media and
audiovisual sector
7
Encourage innovation in
7 agriculture
Promote innovation in the health
4 sector
Encourage innovation in the food
5 sector
Reinforce innovation in the
3 transport sector
Direct EU innovation policies
Stimulate innovation in the
2 fisheries sector
Maintain innovation in the
1 nuclear sector
Increase innovation in security
1
6 Develop innovation in regions
4 Foster innovation in
neighbouring countries
3 Stir innovation among youth
2 Improving innovation in third
countries
2 Evaluate innovation policies of
accession countries
1
Fill up the scarcity of
researchers
3
Promote innovation for
knowledge based economy
0 2 4 6 8
Frequency of EU documents on innovation
Figure 5. EU (European Union) Direct Innovation Policy Design for 2006
Commission’s directorates and Parliament’s committees technology policy, the main policy protagonists are those
dealing with education and research. Others, however, in directorates of the Commission and committees of the
charge of health, defense, energy, transport, and environ- Parliament that deal with applied science and procure-
ment may also play a role since they organize their own ment of technologies. In innovation policy, the main pro-
research communities. Finance plays a role when it tagonists are those directorates of the Commission and
comes to deciding the budget allocation for research. In committees of the Parliament that deal with enterprise.
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9. Rodriguez, Montalvo / INNOVATION POLICIES 475
Provide training and education
as sources of innovation
Enforce environmental
15 regulation to spur innovation
Support culture for creativity and
7
innovation
6 Use innovation degree for trade
Indirect EU innovation policies
3
Respect democracy and human
rights to support innovation
2
Promote standardisation to
2 boost innovation
2 Foster employment and
productivity to achieve
innovation
1
Use information technology for
innovation
1
Meet the development goals to
1 generate innovation
1 Enforce noncontractual
obligations for innovation
Enforce intellectual property
0 5 10 15 20 rights for innovation
Frequency of EU documents on innovation
Figure 6. EU (European Union) Indirect Innovation Policy Design for 2006
Models for Innovation Policies market failures such as extensive externalities, high
transaction costs, and asymmetric information. The mis-
Innovation policy models are referred to in this sec- sion paradigm limits innovation policy to the mission of
tion to illustrate how the historical context played a role government agencies but does not confine it to
in their construction. Bozeman (2000) modeled three defense. The cooperation paradigm fosters technology
paradigms differentiated by policy legitimization, viz. transfer.
market failure, mission, and cooperation (see Table 5). European innovation policies have been increasingly
The market failure paradigm limits innovation policy to differentiated in terms of scope and instruments since the
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10. 476 BULLETIN OF SCIENCE, TECHNOLOGY & SOCIETY / December 2007
Table 5. Bozeman Models
Model Market Failure Mission Cooperative Technology
Core assumptions (1) Markets are the most efficient (1) The government role should be (1) Markets are not always the most
allocation of information and closely tied to authorized efficient route to innovation and
technology. programmatic missions of economic growth.
(2) Government laboratory role agencies. (2) Global economy requires more
limited to market failures such (2) Government R&D is limited to centralized planning and broader
as extensive externalities, high missions of agencies, but not support for civilian technology
transaction costs, and confined to defense. University development.
information distortions. Small R&D supports traditional roles of (3) Government laboratories and
mission domain, chiefly in land grant universities such as universities can play a role in
defense. Universities provided agricultural or engineering developing technology, especially
basic research, in line with extension, manufacturing precompetitive technology, for use
private sector undersupply due assistance, and contract research in the private sector.
to market failure (inability to for defense or energy research.
appropriate directly the results (3) Government should not compete
of basic research). with private sector in innovation
(3) Innovation flows from and to and technology. But a
private sector; minimal government or university R&D
university or government role. role is a complement.
Peak influence Highly influential during all 1945-1965; 1992-present 1992-1994
periods.
Policy examples Deregulation; contraction of Creation of energy policy R&D, Expansion of federal laboratory roles
government role; R&D tax agricultural labs, and other such and university role in technology
credits; capital gains; tax roll broad mission frameworks. transfer and cooperative research
back. Little or no need for and other technology-based
federal laboratories except in economic development programs.
defense support.
Theoretical roots Neoclassical economics. Traditional liberal governance with Industrial policy theory, regional
broad definition of government economic development theory.
role.
Source: Bozeman (2000).
Note: R&D = research and development.
1950s. Rothwell and Dodgson (1992) modeled them diffusion, managerial, and systemic (see Table 7). The
according to a historic approach differentiated by the specific instruments are shown in Table 8.
degree of coordination between science and industrial
policy makers (see Table 6). They displayed three Science, Technology, and Innovation Policies
phases, viz. 1950s and 1960s, mid-1970s to early 1980s,
and early 1980s to early 1990s. The three phases were This section describes the meanings of constructs
characterized by the degree of coordination of science used in innovation policy studies. Firstly, science can be
and industrial policy makers, namely, little, increasing, conceptualized as a mode of knowledge. In the domain
and complete coordination, respectively. or neighborhood, knowledge is just one member of a
Smits and Kuhlmann (2002) also modeled whole cluster of closely related entities, such as fancy, sus-
European innovation policies from a historic stand- picion, surmise, awareness, information, opinion, belief,
point but they differentiated them by the primary goal conviction, and so on, according to Ziman (2005). He
of such policies. The 1970s were characterized by a arranged them in increasing order of credibility to indi-
financial goal for stimulating research and develop- cate that knowledge is just the limit point of that set. A
ment, the 1980s by diffusion or technology transfer, feature of knowledge is the notion of consensus, which
the 1990s by managerial gaps in running businesses, Kusch (2004) envisages as precisely the elusive endpoint
and the 2000s by systems for facilitating change. where knowledge is indeed achieved.
In particular, innovation policy instruments in use in What distinguishes science from other modes of
all EU and preaccession countries were classified by Smits systemic inquiry is its distinctive method: the scien-
and Kuhlmann (2002) into four categories: financial, tific method. In particular, technology is science in
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11. Rodriguez, Montalvo / INNOVATION POLICIES 477
Table 6. Rothwell and Dodgson’s Models
1950s and 1960s Science policy Industrial policy Firm size emphasis
• Scientific education • Grants for R&D • Emphasis on large firms and industrial
• University research • Equipment grants agglomeration
• Basic research in • Industrial restructuring • Creating national “flagship” companies
government • Support for collective • Public R&D funds go mainly to
laboratories industrial research large companies
• Technical education • Paucity of venture capital
and training
Little coordination or active collaboration between science policy makers and industrial policy makers
Mid 1970s to Innovation policy
early 1980s • Some concern over lack of university-industry linkages
• Grants for innovation
• Involving collective research institutes in product development
• Innovation-stimulating public procurement
• Increasing interest in SMEs
• Many measures introduced to support innovation in SMEs
• Continuing paucity of venture capital
Increasing interdepartmental coordination
Early 1980s to present Technology policy
• Increased emphasis on stimulating university-industry linkages
• Increased emphasis on “strategic” research in universities
• Selection and support of generic technologies
• Growth in European policies of collaboration in precompetitive research
• Emphasis on intercompany collaboration
• Emphasis on the creation of new technology-based firms
• Growing availability of venture capital
Interdepartmental initiatives
Growing interest in accountability and in measures for evaluating the effectiveness of public R&D policies
Increasing concern over growing regional economic disparities
National and local government initiatives to enhance R&D
Potential of the less-developed regions: accelerated establishment of regional technology infrastructures
(e.g., science parks, technopoles, innovation centers)
Source: Rothwell and Dodgson (1992).
Note: R&D = research and development; SMEs = small- and medium-sized enterprises.
application; science in action is research (Ziman, major sources of research questions, emphasis on cogni-
2000). The instrumental attitude to science is summed tive or operational problems, and focus on science and
up by the hybrid scientific research and technological technology (Spiegel-Rösing, 1977). Science and tech-
development using the acronym R&D. This linear nology studies started as a movement with a critical view
model locates science at the upstream and innovation of scientific and technological development and its
at the downstream. impact on society. Later, this movement turned into an
The supposed role of research is to produce, by any academic field more interested in knowledge creation,
feasible means, whatever knowledge is required, or having taken approaches from sociology, philosophy,
seems likely to be required, in order to satisfy an and history.
actual, or envisaged, material need. Industrial R&D The science and technology policy was established as
and other forms of applied science do indeed share the an area of government intervention in the immediate
same norms also sometimes found inside large gov- aftermath of World War II. Initially, the main area of
ernmental laboratories. Industrial R&D and academic involvement was just science. In the 1950s and 1960s,
science are culturally very different. the focus was on institution building and expansion of
Science and technology studies and policy analysis policy for science. In the 1970s, the application and uti-
have been divided because of their disciplinary origins, lization of science as a policy were emphasized, with
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12. 478 BULLETIN OF SCIENCE, TECHNOLOGY & SOCIETY / December 2007
Table 7. Development of European Innovation Policy
Primary Goal Client Content Process System
Financial (1970s) stimulating R&D one-to-one private R&D subsidy
firm
Diffusion (1980s) transfer of one-to-one private science subjects limited to specific
knowledge and firm (public formal technical project
technological institution)
competence
Managerial gap support running a one-to-one social science limited to specific organizing small chains
(1990s) business one-to-few formal consultancy project and clusters
private firm tacit demand articulation management interfaces
strategy development
Systemic (late facilitating change chains networks science, social management system organizer
1990s) systems science complex project system builder
formal strategy and vision management interfaces
tacit development identifying, mobilizing,
strategic demand articulation involving users
intelligence stimulate learning guarding democratic
stimulate experimenting content
developing infrastructure
strategic intelligence
Source: Smits and Kuhlmann (2002).
Note: R&D = research and development.
Table 8. Innovation Policy Instruments From EU Member technology thereby emerging more clearly as an area of
States and Accession Countries concern. In the 1980s, there was a shift to innovation pol-
Type of Instrument Specific Instrument icy by removing the distinction between science and
technology. In the 1990s, basic research became inti-
Financial financing mately intertwined with the production of goods and
taxation
strengthening company research
technological development.
start-up technology-based companies Science and technology policy analysis is concerned
Diffusion mobility with the governance, direction, and promotion of science
absorption technologies by SMEs and technology in the real world of science and technol-
Managerial mobility ogy (Salazar-Acosta, 2005). Science and technology pol-
innovation and management
start-up technology-based companies
icy analysis moved between different models and
absorption technologies by SMEs theories from political science, economics, and manage-
strategy, vision of R&D ment. The terms science, basic research, and academia
Systemic Dynamic: have been used interchangeably. In addition, the terms
raising public awareness technology, applied research, and industry have also
promotion of clustering and
been employed in a similar manner.
cooperation for innovation
cooperation research, universities, This semantic confusion has helped to conceal
companies important differences between them. To reduce the
Static (infrastructure): current state of confusion, we provide the following
public authorities clarifications. Traditional literature has been used to
competition
distinguish between basic and applied research, with
protection of intellectual property
rights basic research being focused on questions of funda-
administrative simplification mental scientific interest and applied research focused
legal and regulatory environment on questions of usefulness and applications.
education and training Stokes (1997) modeled research according to the con-
Source: Smits and Kuhlmann (2002). sideration of usefulness and the quest for fundamental
Note: EU = European Union; R&D = research and development; understanding. If there is an application but no quest for
SMEs = small- and medium-sized enterprises. fundamental understanding, then the research falls into
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13. Rodriguez, Montalvo / INNOVATION POLICIES 479
Edison’s quadrant. If there is no consideration of useful- account the combination of heterogeneous factors whose
ness, but there exists a quest for fundamental under- interactions produce—or fail to produce—innovation.
standing, then the research falls into Bohr’s quadrant. If Sociology of science developed this perspective by
there is both consideration of usefulness and fundamen- rejecting the retrospective view that suppresses moments
tal understanding, then the research falls into Pasteur’s of uncertainty and sees creation only as a series of
quadrant. inevitable stages moving from the abstract to the con-
Research can be conducted in industrial, governmen- crete, from the idea to its concretization (Akrich, Callon,
tal, or academic organizations. Basic research is not the & Latour, 1988). Translation of and through technical
monopoly of universities; some companies carry out instruments is a constant process of relating information
basic research as well. Furthermore, applied research is and protagonists and of regularly reinterpreting the sys-
not only found in industry; academia also pursues tems thereby created.
applied research. Nonetheless, the labels of basic and Public policy instrumentation, in general, and innova-
applied research are changing. A priori definitions of tion policy instrumentation, in particular, are therefore
polar ideal types are vague, imprecise, and awkward for means of orienting relations between political society
empirical operationalization in postmodern science (via the administrative executive) and civil society (via
(Callon, 1997; Kidd, 1965; Latour, 1993). its administered subjects), through intermediaries in the
Science and technology are distinct branches of form of devices that mix technical components (measur-
knowledge and distinct communities, with different ing, calculating, the rule of law, procedure) and social
research problems and methods, responding to differ- components (representation, symbol). This instrumenta-
ent incentives. Technology involves much more than tion is expressed in a more-or-less standardized form—a
science, and innovation involves much more than required passage for public policy—and combines oblig-
technology. Innovations do not always involve the ations, financial relations (tax deductions, economic aid),
application of technology (Metcalfe, 2000). It is inad- and methods of learning about populations (statistical
equate to think of innovation in technological terms observations).
alone (Dodgson & Bessant, 1996).
References
Concluding Comments Akrich, M., Callon, M., & Latour, B. (1988). A quoi tient le suc-
cès des innovations? Annales Des Mines, 4, 29.
From a policy point of view, it is easier to talk about Alic, J. (2002). Policies for innovation: Learning from the past. In
science and technology as a single concept, because V. Norberg-Bohm (Ed.), The role of government in technology
technology is applied science. When the focus of policy innovation: Insights for government policy in the energy sec-
is on innovation in Schumpeterian terms, it became tor. Cambridge, MA: Harvard University, Belfer Center for
Science and International Affairs.
clear that this catch-all concept included more than Alic, J., Mowery, D., & Rubin, E. (2003). U.S. technology and
science and technology. Innovation policy is therefore innovation policies: Lessons for climate change. Arlington,
more generic than science, technology, and research VA: Pew Center on Global Climate Change.
policies. In this sense, innovation polices may include Bernelmans-Videc, M., Rist, R., & Vedung, E. (1998). Carrots,
nontechnological aspects such as organizational learning sticks and sermons: Policy instruments & their evaluation.
New Brunswick, NJ: Transaction.
and commercialization.
Birkland, T. (2001). An introduction to the policy process: Theories,
The issue of the choice of instruments is intimately concepts, and models of public policy making. Armonk, NY:
linked to the issue of policy design, which means the Sharpe.
development of a systematic understanding of the selec- Blind, K., Bührlen, B., Menrad, K., Hafner, S., Walz, R., & Kotz, C.
tion of instruments and an evaluative dimension (Linder (2004). New products and services: Analysis of regulations shap-
& Peters, 1984). Scholars of the history of technology ing new markets. Karlsruhe, Germany: Fraunhofer ISI.
Bozeman, B. (2000). Technology transfer and public policy: A
and the sociology of science have denaturalized techni- review of research and theory. Research Policy, 29, 627-655.
cal objects by showing that their progress relies more on Braczyk, H., Cooke, P., & Heidenreich, M. (Eds.). (1998). Regional
the social networks that form around them than on their innovation systems: The role of governances in a globalized
own characteristics. Simondon (1958) studied innova- world. London: University College London.
tion not as the materialization of an initial idea but as an Breschi, S., & Malerba, F. (1997). Sectoral systems of innovation:
Technological regimes, Schumpeterian dynamics and spatial
often chaotic dynamic that sets information, adaptation
boundaries. In C. Edquist (Ed.), Systems of innovation: Technolo-
to constraints, and arbitration on a path of convergence gies, institutions, and organizations. London: Pinter.
between divergent routes of development. He went on to Callon, M. (1997). Actor-network theory: The market test. Keele, UK:
talk about the process of concretization, taking into Keele University, Centre for Social Theory and Technology.
Downloaded from http://bst.sagepub.com by on September 22, 2009
14. 480 BULLETIN OF SCIENCE, TECHNOLOGY & SOCIETY / December 2007
Carlsson, B. (Ed.). (1995). Technological systems and economic Kidd, C. (1965). Basic research: Description versus definition. In
performance: The case of factory automation. Dordrecht, N. Kaplan (Ed.), Science and society. Chicago: Rand McNally.
Netherlands: Kluwer. Kuhlmann, S. (2001). Future governance of innovation policy in
Carlsson, B. (Ed.). (1997). Technological systems and industrial Europe: Three scenarios. Research Policy, 30, 953-976.
dynamics. Dordrecht, Netherlands: Kluwer. Kuhlmann, S. (2002). Future governance of innovation policy in
Carlsson, B., & Stankiewicz, R. (1991). On the nature, function Europe. In 2003 proceedings of the Innovation Policy Workshop
and composition of technological systems. Journal of on Future Directions of Innovation Policy in Europe (Innovation
Evolutionary Economics, 1, 93-118. Papers No. 31). Brussels, Belgium: European Commission.
Cooke, P., Gomez Uranga, M., & Etxebarria, G. (1997). Regional Kusch, M. (2004). Knowledge by agreement: The programme of
innovation systems: Institutional and organisational dimen- communitarian epistemology. Oxford, UK: Clarendon.
sions. Research Policy, 26, 475-491. Lascoumes, P., & Le Gales, P. (2007). Introduction: Understanding
den Hertog, P., & de Groot, H. (2005). Horizontal co-ordination of public policy through its instruments—From the nature of instru-
innovation policies: The case of information society in ments to the sociology of public policy instrumentation. Gover-
Netherlands. In Governance of innovation systems: Case stud- nance, 20, 1-21.
ies in cross-sectoral policy. Paris: Organisation for Economic Latour, B. (1993). We have never been modern. London:
Co-operation and Development. Harvester Wheatsheaf.
Dodgson, M., & Bessant, J. (1996). Effective innovation policy: A Linder, S., & Peters, B. (1984). From social theory to policy
new approach. New York: International Thomson Business Press. design. Journal of Public Policy, 4, 237-259.
Doty, D., & Glick, W. (1994). Typologies as a unique form of Lundvall, B. (1992). National systems of innovation: Towards
theory building: Toward improved understanding and model- a theory of innovation and interactive learning. London:
ling. Academy of Management Review, 19, 230-251. Pinter.
Edquist, C. (1997). Systems of innovation approaches: Their emer- Lundvall, B., & Borrás, S. (2005). Science, technology, and inno-
gence and characteristics. In C. Edquist (Ed.), Systems of innova- vation policy. In J. Fagerberg, D. Mowery, & R. Nelson (Eds.),
tion: Technologies, institutions, and organizations. London: Pinter. The Oxford handbook of innovation. Oxford, UK: Oxford
Edquist, C. (2001). The system of innovation approach and inno- University Press.
vation policy: An account of the state of the art. Aalborg, Lundvall, B., Johnson, B., Andersen, E., & Dalum, B. (2002).
Denmark: Nelson Winter Conference DRUID. National systems of production, innovation and competence
Edquist, C., & Johnson, B. (1997). Institutions and organizations in building. Research Policy, 31, 2132-2231.
systems of innovation. In C. Edquist (Ed.), Systems of innovation: Luria, S., Gould, S., & Singer, S. (1981). A view of life. Menlo
Technologies, institutions, and organizations. London: Pinter. Park, CA: Benjamin-Cummings.
European Commission. (1995). Green paper: Innovation. Commu- Malerba, F. (2002). Sectoral systems of innovation and produc-
nication, 688. tion. Research Policy, 31, 247-264.
European Commission. (2000a). Innovation policy in a knowledge- March, J., & Olsen, J. (1996). Institutional perspectives on politi-
based economy. Luxembourg: Office for Official Publications of cal institutions. Governance, 9, 247-264.
the European Communities. Metcalfe, S. (2000). Science policy and technology policy in a
European Commission. (2000b). Towards a European research competitive economy. In C. Edquist & M. McKelvey (Eds.),
area. Communication, 6. Systems of innovation: Growth, competitiveness and employ-
European Commission. (2001). European governance: A white ment. Cheltenham: Elgar Reference Collection.
paper. Communication, 428. Meyer-Krahmer, F., & Kuntze, U. (1992). Bestandsaufnahme der
European Commission. (2003). Innovation policy: Updating the Forschungs—und Technologiepolitik. In K. Grimmer, J. Häusler,
Union’s approach in the context of the Lisbon strategy. S. Kuhlmann, & G. Simonis (Eds.), Politische Techniksteuerung—
Communication, 112. Forschungsstand und Forschungsperspektiven. Leske: Opladen.
European Convention. (2002). Final report of working group VI Nelson, R. (1993). National innovation system. New York: Oxford
on economic governance. Convention, 357. University Press.
European Council. (2000). Lisbon European Council: Presidency Ohmae, K. (1993). The end of the nation state: How region states
conclusions. Brussels, Belgium: Author. harness the prosperity of the global economy. New York: Free
Georghiou, L. (2001). Evolving frameworks for European collabora- Press.
tion in research and technology. Research Policy, 30, 891-903. Rogers, E. (1995). Diffusion of innovations. New York: Free Press.
Hart, D. (2001). Antitrust and technological innovation in the US: Rothwell, R., & Dodgson, M. (1992). European technology policy
Ideas, institutions, decisions, and impacts, 1890–2000. Research evolution: Convergence towards SMEs and regional technol-
Policy, 30, 923-936. ogy transfer. Technovation, 12, 223-238.
Jaffe, A., Newell, R., & Stavins, R. (2003). Technology policy for Rubin, E. (2001). Introduction to engineering and the environ-
energy and the environment. In A. Jaffe, J. Lerner, & S. Stern ment. Boston: McGraw-Hill.
(Eds.), Innovation policy and the economy. Cambridge, MA: Salazar-Acosta, M. (2005). Theories on technology and society.
National Bureau of Economic Research. Vancouver: Simon Fraser University, Centre for Policy
Johnson, A. (2001). Functions in innovation systems approaches. Research on Science and Technology.
Aalborg, Denmark: Nelson Winter Conference DRUID. Schumpeter, J. (1939). Business cycles: A theoretical, historical,
Kaiser, R., & Prange, H. (2004). Managing diversity in a system and statistical analysis of the capitalist process. New York:
of multi-level governance: The open method of co-ordination McGraw-Hill.
in innovation policy. Journal of European Public Policy, 11, Shapira, P., & Klein, H. (2001). Innovations in European and US
249-266. innovation policy. Research Policy, 30, 869-872.
Downloaded from http://bst.sagepub.com by on September 22, 2009
15. Rodriguez, Montalvo / INNOVATION POLICIES 481
Simondon, G. (1958). Du mode d’existence des objets techniques. Ziman, J. (2000). Real science: What it is and what it means.
Paris: Aubier. Cambridge, UK: Cambridge University Press.
Simpson, M. (2006). Plant systematics. Amsterdam: Elsevier Ziman, J. (2005). Knowledge by agreement. Minerva, 43, 289-295.
Academic Press.
Smits, R., & Kuhlmann, S. (2002). Strengthening interfaces in
innovation systems: Rationale, concepts and (new) instru- Victor Rodriguez is a researcher at the Innovation Policy
ments. In Proceedings of the workshop “New challenges and Group of the Netherlands Organisation for Applied
new responses for S&T policies in Europe.” Brussels, Belgium: Scientific Research TNO. His main research interests are in
European Commission, Directorate General for Research. the economics of intellectual property rights, the economics
Spiegel-Rösing, I. (1977). The study of science, technology of science, and research policy.
and society (SSTS): Recent trends and future challenges. In
I. Spiegel-Rösing & D. de Solla Price (Eds.), Science, technol-
ogy and society. Beverly Hills, CA: Sage.
Carlos Montalvo is a senior researcher at the Innovation
SQW. (2006). Exploring the relationship between environmental Policy Group of TNO. His research activities and interest
regulation and competitiveness: A literature review. London: focus on innovation and competitiveness, the evaluation of
SQW Economic and Management Consultants. S&T programs, and the application of behavioral and sys-
Stokes, D. (1997). Pasteur’s quadrant: Basic science and techno- tem dynamics models to assess the impact of policy and
logical innovation. Washington, DC: Brookings Institution. regulation on innovation.
Downloaded from http://bst.sagepub.com by on September 22, 2009
