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Coevolution of industry
and its institutional environment
First complete version
March 6, 2006
Mikko Jouhtio
Helsinki University of Technology
Institute of Strategy and International Business
TU-91.167 Seminar in Business Strategy and International Business

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Abstract
When Charles Darwin introduced his theory of evolution in 1859, it would have been
hard for him to predict that in future his principles of natural selection would be
applied to economics, among others. Adaptability has become a strategic imperative
for the modern firm to survive, just as it has always been for biological entities.
In biology, the term coevolution refers to successive changes among two or more
ecologically interdependent but unique species that their evolutionary trajectories
become intertwined over time. The concept of coevolution has been employed in
explaining very different type of interactions. This paper focuses on describing the
literature study of coevolution of industry and its institutional environment, aiming to
describe how the coevolution framework can explain the influencing the industry and
its institutional environment have to each other.
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Table of Contents
Abstract..........................................................................................................................................2
1 Introduction ...............................................................................................................................4
2 Evolution theory........................................................................................................................4
2.1 Industry evolution theory.................................................................................................6
3 Coevolution theory...................................................................................................................7
3.1 Coevolutionary thinking in economics...........................................................................8
4 Role of institutions in coevolutionary theories...................................................................10
4.1 Social technologies as institutions .................................................................................10
4.2 Coevolution of institutions and technological change ...............................................11
4.3 The influence of public research on industrial R&D...................................................14
4.4 Applications of institutional coevolutionary theory...................................................18
5 Discussion ................................................................................................................................20
References....................................................................................................................................24
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1 Introduction
This paper focuses on describing the literature study of coevolution of industry and its
institutional environment. Study is conducted as a seminar assignment in the Seminar
of International Business at the Helsinki University of Technology during the fall and
spring terms 2005 - 2006. Study is mainly based on the literature and research articles
found in scientific databases.
The purpose of this paper is twofold. The first objective is to gain comprehensive
understanding about industrial evolution theory in general and especially about the
coevolutionary thinking in economical studies. Secondly, more focus is given to the role
of institutions in (co)evolutionary theories, with paying attention particularly to the
influence of public research. The research problem can be expressed as: How can the
coevolution framework explain the influencing the industry and its institutional environment
have to each other?
2 Evolution theory
In 1859, Charles Darwin introduced his now-famous theory of evolution in On The
Origin of Species (Darwin, 1859). The evolution theory describes how the evolution of
species is based on the natural selection process, which selects the most suitable
individuals to pass their characteristics onward via natural selection process. Although
Darwin is commonly seen as the “father” of evolution theory, evolutionary linguistics
theories existed long before him (Murmann, 2003). In matter of fact, Darwin illustrates
his theory also by taking the case of languages (Darwin, 1859). More recently, Hull
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(1995) has concluded that formal structures of evolution of language and biological life
are essentially same. Indeed, the logical structure of an evolutionary theory is of much
more general purpose than solely biological theory, as Murmann (2003) notes with
references to Campbell (1969), Dawinkins (1976), Dennet (1995), and Hull et al. (2001).
As the example of linguistics clearly shows, evolutionary explanations can be applied to
other fields of science, besides biology. In his article Hogdson (2002) studies the
applicability of evolutional theories into economical sciences, drawing on number of
thinkers such as Walter Bagehot (1872), William James (1880), David Ritchie (1890,
1896), Samuel Alexander (1892), Thorsten Veblen (1899, 1919) and James Baldwin
(1909). These thinkers saw the Darwinian principles of natural selection applicable also
to mental, moral or even social evolution. Nature, society and industry have a lot in
common: they are all open, complex systems, which evolve via variation, inheritance
and selection (Hogdson, 2002). Van de Bergh and Gowdy (2000) characterizes evolution
as “disequilibrium and qualitative (structural) change that is irreversible and unpredictable, can
be gradual and radical, and is based on micro-level diversity (variation) and selection, as well as
macro-level trends and schocks (“large scale accidents”).” Murmann (2003) crystallizes the
key point of evolution theory as “descent with modification” by which he means the
general principle that new things can only come about by changing and conjoining
existing things.
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2.1 Industry evolution theory
Van de Bergh and Gowdy (2000) suggest three reasons why evolutionary thinking is
important to economics: (1) industrial economies have not shown movement towards
steady state as the dominant economic growth theory would imply; (2) economic
systems have a great capacity for sustained learning and adaptation; (3) evolution can
be observed in horizontal organizational structure of the economy, incorporating
science, technology, businesses, markets, the legal system, consumer preferences, and
institutions. Murmann (2003) sees two reasons why evolutionary industry theories have
been developed: (1) to explain industrial and organizational structures in terms of the
consequences of the agent’s actions, besides its intentions; (2) to recast the fundamental
assumptions of how humans make decisions and behave. Adaptability has been a
strategic imperative for biological entities in order to survive, and now it has become a
similar strategic imperative for the modern firms. Nowadays, in dynamic business
environment, firms need to establish their strategic planning on future expectations and
awareness of their environment instead of traditional Newtonian cause-and-effect
model (Rabkin and Bradford, 2002).
Like any other evolutionary theory, industry evolution theory needs to specify the
primary selection processes among the processes that transform a population of
particular entities. For example, in case of populations of industrial firms, Murmann
(2003) identifies births and deaths of individual firms and managerial decision making
(such as changing of strategies and organizational structures) as two key selection
processes.
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3 Coevolution theory
The term coevolution originates in biology and refers to successive changes among (two
or more) ecologically interdependent but unique species so that their evolutionary
trajectories interlace over time, adapting to each other. This results in an ecosystem of
partially interdependent species that adapt together. This interdependence can be either
symbiotic, (the species help each other), commensalist, (one species takes advantage of
the other), or competitive (one species drive out the other, or both species may evolve
into distinct, noncompetitive niches). (Eisenhardt and Galunic, 2000). A particular type
of symbiotic interdependence is the “arms race”, which means that characteristics of
species respond positively to each other (e.g. predation will select faster running prey,
which will select faster running predators) (van den Bergh and Stagl, 2003).
Ecosystems are visualized as having fitness landscapes: mountainous terrains where
higher peaks represent the more successful survival strategies. The smoother the fitness
landscape is, the less there is complexity, differentiation among competitors, and
uncertainty of change. (Rabkin and Bradford, 2002). Kauffman (1993) describes
coevolution as a relationship where one partner deforms the fitness landscape of the
second partner and vice versa, resulting in some of the above mentioned types of
interdependencies by altering the average fitness of both partners. Baum (1999)
describes same idea with different terminology by speaking of supercompetitive, partly
competitive, synergistic and independent coevolutionary systems.
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3.1 Coevolutionary thinking in economics
Just as in case of the “ordinary” evolution, scholars have recognized that also
coevolution exists in various phenomena, besides biological life (Eisenhardt and
Galunic, 2000). The popularity of coevolutionary analysis in organization science over
the last decade has a lot to do with the realization that it is almost impossible to
understand the behavior and performance of organizations without studying how their
environments change (Murmann, 2003). The concept of coevolution has been employed
in explaining very different type of interactions: biological-cultural, ecological-
economic, production-consumption, technology-preferences, behavior-institutional, and
human genetic-cultural (van den Bergh and Stagl, 2003). Coevolution has played part in
describing for instance emergence of bureaucratic forms of organizations in the
beginning of the industrial age, replacement of medieval guilds by mercantilist
factories, and dynamic interactions between selection and adaptation at intracorporate
level of analysis (Lewin and Volberda, 1999). Recently, the concept of coevolution has
been applied in research of industrial leadership (Nelson, 1995), technological change
(Mokyr, 2002), and development of firms (Lewin et al., 1999).
Norgaard (1984, 1994) was first to introduce coevolution in a socio-economic context,
regarding it as reflecting long-term feedbacks that occur between five main subsystems:
knowledge, values, organization, technology and environment. Variation within each
subsystem gets strong influence from selection conditions that other subsystems
provide (van den Bergh and Stagl, 2003). Various coevolutionary theories in economics
have been followed. For instance, Murmann’s (2003) coevolutionary theory links
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industrial, technological, and institutional dynamics. Lewin et al. (1999) present a
similar theory of coevolution of organizations, industries, and institutional and extra-
institutional environments, assuming distinct and interdependent patterns of change.
Lewin and Volberda (1999) discuss of the essential properties of coevolution and on
basis of that identify requirements that distinguish coevolutionary research from non-
coevolutionary research, pointing out following key issues that should be considered
when applying coevolutionary perspective: (1) use longitudinal time series to study
organization adaptations over a long period of time; (2) examine organization adaptation
within a historical context of the firm and its environment; (3) consider multidirectional
causalities between micro- and macroevolution, and between other system elements; (4)
incorporating mutual, simultaneous, lagged, and nested effects that can produce
counterintuitive changes in affected variables; (5) consider path dependence, which enables
and restricts adaptation at the firm level and at the population level; (6) incorporate
changes occurring at the level of different institutional systems within which firms and
industries are embedded; (7) accommodate economic, social, and political macrovariables
that may change over time and influence the deep structure within which micro- and
macroevolution operate, identifying and incorporating their effects (see also Lewin et.
al, 1999). However, there are some challenges in conducting coevolution research and
addressing those key issues. First of all, longitudinal coevolutionary research requires
richer variety of methods and techniques than traditional time series methods.
Appropriate time series data may also be inaccessible. Moreover, if the appropriate
data is accessible, the research and assembly of large-scale primary data sequences
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requires more time and resources than what is usually available for most researchers.
There are also certain issues with the selection of the time horizon for conducting a
coevolutionary study, as the “proper” practice has not yet been determined by
researchers. (Lewin and Volberda, 1999)
4 Role of institutions in coevolutionary theories
4.1 Social technologies as institutions
As the knowledge and know-how needed to perform complex tasks is often very
divided and widely distributed among different individuals, it needs to be brought
together and coordinated in order to be effective. Nelson and Sampat (2001) use the
term social technologies to describe the knowledge of the elements that are needed and
of how to coordinate their combined operation. The term is associated with effective
structures of division of labor, procedures for task coordination and management.
Nelson and Sampat (2001) suggest associating the term institution with a social
technology that has come to be regarded by the relevant social group as standard in the
context. Hence this concept sees the institutions as routines, specific ways of playing a
game. These institutions differ in the extent to which they are supported by norms and
values of the society (Nelson and Sampat, 2001). Pelikan (2003) has criticized that the
labeling of social technologies as institutions is “terminological waste”, arguing that this
sort of naming narrows the concept of institution and hinders access to important
institutional areas such as those concerning property rights, law and economics, and
reform policies. However, Pelikan notes that his disagreement with Nelson and Sampat
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(2001) has quite merely to do with the use of terminology within the concept, pointing
out that he is not disagreeing with the actual concept of social technologies.
The social and physical aspects of technologies are often embracing: complex mixture of
physical technologies are employed by a team in which each member must do assigned
tasks in concord with what other members are doing. Thus, the practice and
understanding coevolve in the process of technological advance. Development of new
practice (physical technology) generally brings with it a wider body of new
understanding (social technology), which in turn provides clues and opportunities for
further advance of technological practices. (Nelson, 2003). However, the process of
advancing technology still remains evolutionary, as efforts to invent something new
almost invariably reach well beyond what is known with certainty (Nelson and Winter,
2002).
4.2 Coevolution of institutions and technological change
Based on review of several studies on long term industry evolution, Nelson (1999)
argues that the industry life cycle theory does not take enough into account the
important role of institutions shaping the industries. During the last couple of decades,
institutional ideas in economics have been represented by many scholars (see for
example Hodgson, 1988, 1994, 1998, Eggertsson, 1990, Ruthenford, 1994, Langlois, 1986,
1989). The lately risen new interest in institutions as a factor shaping economic
performance can be seen as a return to as far as to Adam Smith and his theories (1776).
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Murmann (2003) places national institutions and technology into spotlight in his
coevolution framework, arguing especially that so far the critical missing piece in
institutional analysis has been the analysis of the creation of institutions. Murmann’s
precise definition for term coevolution is following: “two evolving populations coevolve if
and only if they have significant causal impact on each other’s ability to persist” (2003: 22).
Coevolutionary dynamics can create a self-reinforcing process that transforms small
initial differences in the performance of national institutions into larger differences over
time. Murmann defines coevolution as a phenomenon where multiple things are jointly
evolving, instead of a more commonly used definition of parallel development of just
two entities. Two parties in coevolutionary relationship are linked by bidirectional
causality. As coevolution can be easily confused to such things as sequential
adaptations from different causes or simultaneous adaptation to the same environment,
it is necessary to try to recognize cross-flows between separate systems in order to find
evidence for reciprocal influences.
In more general level, Pelikan (2003) describes the importance of both directions of the
interdependent relationship between institutions and technological change. The
influence of technological change on institutions can be described by following two
links: (a) efficient use of the production methods and/or the products of a new
technology require new institutions; (b) a new technology can enable implementing of
novel, superior institutions that were previously unfeasible or prohibitively expensive.
The need of refinements of property rights as an influence of new information
technologies is a good example of the former linkage, whereas the latter link can be
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exemplified by increase of competition in telecommunication industry as a result of
technological innovations. The causality of both links is only indirect and therefore it
may not be a priori known which institutional changes are required by certain
technological change, nor which novel institutions certain technological change makes
advantageous to implement. The requirement for institutional change to happen is that
some agents (“institutional entrepreneurs”) have the knowledge to design it and the
initiative to put that design to work. The first mentioned linkage results more likely in
actual institutional change, as possible relative or absolute losses caused by lack some of
the rules needed for efficient use of a new technology function as strong incentives to
search for design of such rules. However, there can also be strong incentives against
institutional change. (Pelikan, 2003).
Institutions influence on technological change through following four links: (c) the
influences on the freedoms of the organization that affect the variety of permissible
technological innovations; (d) the influences on the incentives and disincentives such as
transaction costs that affect the amount of permissible technological innovations that
will actually be tried; (e) the influences on the strictness and speed of the elimination of
the actually tried innovations that affect the likeliness of selecting sound technological
innovations; (f) the influences on correctness of the selection. The causality of this four
links is also indirect. Hence institutions can effectively influence technological changes
only if some agents (such as innovators, entrepreneurs and risk-capital investors) take
the initiative to respond to freedoms and incentives implied by the current institutions
and actually try to realize some technological changes. (Pelikan, 2003).
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4.3 The influence of public research on industrial R&D
Numbers of institutions are involved in technological advance. The role of business
firms is obvious, but recently much attention is also paid to the roles of university
research and government programs. Innovation system is term used to describe a set of
different kinds of institutional actors either at the level of a nation, and industry or a
technology. (Nelson and Winter, 2002). Technological advance has been rapid in fields
that seem to be closely connected to a powerful applied science or engineering
discipline. Strong scientific and engineering knowledge helps to recognize the
promising development paths that are likely to lead to solutions or improvements and
also provides powerful ways of assessing these paths. (Nelson, 2003). The rate of
technological advance in an industry is strongly correlated with the strength of the
sciences on which the R&D in that industry is based on (Nelson and Wolff, 1997). Many
problems that science addresses have been revealed or created by the operation of
technologies. There is a strong symbiosis between the technologies and the focus of
sciences underlying them: the technology tends to move towards where the
understanding is strong and the science can progress by manipulating the aspects of the
technology experimentally. In fields where the technological process has been rapid,
problem solving and inventing is done to a considerable degree in specialized facilities
separated from where the technology is actually employed. (Nelson, 2003).
There has been a call for making the public research to make their science and
engineering more relevant to industry’s needs. Direct contribution of public research to
the R&D activities of a firm has been slight compared to the contribution of the firms in
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the industry, including suppliers and buyers (Cohen et al., 2002). In his survey of 76
firms, Mansfield (1991) found out that 10 percent of new products and processes were
built on academic research conducted within the prior 15 years. Other researches have
come up with same sort of results (see e.g. Adams, 1990), suggesting that public
research is important for industries, although it can take even some decades to become
manifest. There have been arguments that if private firms would invest in basic
research in order to capture the output information, it would limit its distribution and
use by other firms. Thus, public funding of basic research is recommended. (Pavitt,
2001).
So although public research has some influence on industrial R&D, one could argue
that the latency time is rather long. Thus, during the past two decades policymakers
have been encouraging universities and governmental laboratories to
commercialization of developed technologies. Therefore it is not surprising that the
deepening of ties between public research institutions and industry can be seen for
instance in the significance increases of both the patents granted to universities and of
the industry funding of university research in US between the years 1985 and 1998.
(Cohen et al., 2002).
Nowadays public research has a considerable influence on industrial R&D in certain
industries such as pharmaceuticals. The contribution of public research varies across
industries, but in general it plays important role in various manufacturing industries.
Public research is used both to address existing problems and needs and to suggest new
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R&D projects. Table 1 lists industries where public research plays important roles via
these two activities. Large firms are more likely to take advantage of public research
than small firms, with the exception of small start-up firms. (Cohen et al., 2002).
Table 1 Industries where public research plays important role (Cohen et al., 2002)
Public research as a stimulus to the
initiation of a new R&D project
Public research as a knowledge source for
executing a R&D project
pharmaceutical industry
petroleum industry
steel industry
machine tool industry
semiconductor industry
aerospace industry
aerospace industry
car/truck industry
pharmaceutical industry
food industry
paper industry
glass industry
search/navigation equipment industry
Public research contributes to industrial R&D primarily through research findings. The
prototypes generated by public research are exploited in industrial R&D much more
seldom. The knowledge from public research is mainly transferred via the channels of
open science, i.e. publications, reports, public meetings and conferences. Other public
and personal channels such as informal information exchange follow in importance.
The common characteristic in the most important transfer channels is their
decentralized nature and lack of formal institutional links. (Cohen et al., 2002).
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From various fields of public research, the fields of engineering and applied sciences (of
which mainly medical and health science) has biggest contribution to industries. From
basic sciences chemistry, and to some extent physics, mathematics and biology, have
importance to industrial R&D. The influence of basic sciences is relatively lower, but on
the other hand they affect the industries also through the applied sciences and
engineering fields that they inform. However, the influences of various fields of public
research vary significantly across different industries. (Cohen et al., 2002).
The availability of skilled labor often accounts for why one nation has an advantage
over another one. Strong national industries are also often supported by highly
specialized supplier industries and supporting institutions such as universities.
(Murmann, 2003). Basic research conducted in universities brings in significant benefits
by training of scientists and engineers. The output of basic research is public domain by
nature and therefore nations can exploit foreign science and technology. However, in
order to understand and to take advantage of the results of basic research performed
elsewhere, substantial investment in institutions, skills, equipment, and networks is
needed. (Pavitt, 2001). It can be seen as waste of resources to focus on field of science
where the required preliminary understanding is weak, as it is then quite unlikely to be
able to develop technology that would perform significantly better than prevailing
practice. Hence it is necessary first to support that sort of (basic) scientific research that
enables the more practical problem to be understood. (Nelson, 2003).
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4.4 Applications of institutional coevolutionary theory
Several studies have examined the role of institutions in coevolutionary theories. A
brief illustration of some of those studies will now follow, with a simple objective to
give some sort of picture of how the institutional coevolutionary theories can be applied
in analysis of real-life cases. Note that not all of the illustrated studies have strong focus
on coevolutionary thinking, as some of the following studies represent more the typical
research of the influences of institutions on technological change without examining the
opposite direction of the relationship. The common denominator to all these studies is
the analysis of longitudinal time series (though not necessary always over relatively
long period of time) within some historical context.
In his study of synthetic dye industry in 1850-1914, Murmann (2000, 2003; Murmann
and Homburg, 2001) compares the evolution of that industry in five major producer
countries (Britain, Germany, France, Switzerland and USA) and identifies major
differences in the patterns of industry evolution across national contexts. He identifies
several factors that contributed in the development of the dominance of German firms
in synthetic dye industry: (1) legal environment; (2) availability of crucial skills; (3)
existing industrial infrastructure; (4) economies of scale and scope; (5) technological
dynamics; and (5) positive feedback mechanisms between firms and national
institutions. Murmann also recognizes three specific causal mechanisms that connected
the evolution of national populations of firms with the evolution of national
populations of universities: exchange of personnel, formation of commercial ties and
lobbying on behalf of the other social sphere.
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Santos (2003) analyzes the major changes in the knowledge environment of the
pharmaceutical industry in the postwar period. By knowledge environment he refers to
all the factors, institutions, and events that affect the production, access, dissemination, and
application of the knowledge employed by firms”. Santos states the knowledge environment
in pharmaceutical industry to be influenced, among others, by: (1) the institutional and
organizational mechanisms for the production of new knowledge and for the training of
professionals in universities, research institutions, and industrial research laboratories;
(2) institutionalized mechanisms for dissemination of knowledge via academic and
professional journals, and networks of collaborations among organizations; (3)
regulatory systems determining the possibilities of appropriating novel knowledge; and
(4) sources of funding and incentive mechanisms for the production of new knowledge
and innovation.
Haveman and Rao (1997) examine the institutional and organizational coevolution in
early thrift industry in California between the years 1865 and 1928. They analyze how
various forms of social and economic institutions were built up in tandem with tandem
of the development of organizational forms in industry. The selected industry was
characterized by both strong technical pressure for efficiency and strong institutional
pressure for legitimacy. The main finding of the study is that the coevolution of thrift
organizations and institutions proceeded primarily through selection (births and
deaths) rather than through adaptation (conversions from one entity to another).
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Branerhjelm et al. (2000) compared the evolution of polymer and biomedical clusters in
Ohio, USA and Sweden. These two regions are of similar size, with similar traditions,
similar industrial structure, and similar industrial restructuring challenges but with
different history and institutional arrangements. A wide range of historical and
institutional factors were involved in the rapid growth of these clusters, including
academic institutions, research institutes, public policy agencies, industry associations,
and financial services such as venture capital. The study pointed out the difference of
the educational systems in these two regions, and its influence on the supply of
researchers to the polymer industry: Sweden was recognized to be lacking the critical
mass of academic research that would generate top class technology for the industry.
5 Discussion
The research problem to be answered in this seminar paper was formulated as: How can
the coevolution framework explain the influencing the industry and its institutional
environment have to each other?
This question was approached by first gaining a comprehensive understanding of
evolutionary and coevolutionary thinking in economical studies. As adaptability is
nowadays a strategic imperative for modern firms in order to survive, the evolutionary
thinking has become important to economics. The key issues that should be considered
when applying coevolutionary perspective were pointed out. Using of longitudinal
time series over a long period of time and within a historical context of the firm and its
environment was noted to be highly important. However, the “proper” time span has
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not yet been determined by the scholars. As coevolutionary dynamics can transform
small initial differences in the performance of institutions into larger differences over
time, good understanding of the interplay between industry and its institutional
environment can be highly valuable. Thus there exists a clear demand for
coevolutionary theory as an interpreter of the relationship between industry and its
institutional environment.
Institutions were associated with a social technology that has come to be regarded by
the relevant social group as standard in the context. Hence the institutions are seen as
routines, specific ways of playing a game. The term social technology describes the
knowledge of the elements that are needed and of how to coordinate their combined
operation. The term is associated with effective structures of division of labor,
procedures for task coordination and management. Development of new practice
(physical technology) generally brings with it a wider body of new understanding
(social technology), which in turn provides clues and opportunities for further advance
of technological practices. The links between the both directions of interdependent
relationship of institutions and technological change were identified. An industry can
be understood as a set of both physical and social technologies, which coevolve in the
process of technological advance. So coevolutionary understanding of technology and
institutions has an essential role in comprehending (and to some extent, controlling) the
advance of technology.
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The influences that a specific type of institutions, i.e. public research, has on industrial
R&D and technological change were discussed. Although the industry calls for more
relevant research via applied sciences and engineering, the importance and long-term
results of basic research was also recognized. Public research contributes to industrial
R&D primarily through research findings. The contribution of public research varies
across industries, but in general it plays important role in various manufacturing
industries. Especially in case of certain industries, the significance of supporting
institutions (such as universities) is high, as the availability of skilled labor often
accounts for why one nation has an advantage over another one in a specific industry.
The conducted literature study suggests that the coevolution framework can, and
should, be used to explain the influencing the industry and its institutional
environment have to each other.
Finally, few applications of institutional
coevolutionary theory were briefly reviewed. On the basis of those exemplary studies
and the issues covered in this literature studies, some suggestions for further research
have unfolded. The coevolutionary theory could give interesting viewpoint to the
development of Finnish ITC industry between late 1980s and early 2000s. One could
assume that the Finland’s investment in high quality research and education in
telecommunications and computer sciences has played a significant role in shaping the
competitiveness of Finnish ITC industry and vice versa. Perhaps the coevolutionary
analysis of institutions would also enlighten the current state of the ITC industry in
Finland which has lately been argued to be declining. Perhaps the analysis could also
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clarify whether the research and education in Finnish universities has lost its scope or
not?
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