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Global Innovation Networks: what are they and where can we find them? (Conceptual and Empirical issues)


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The rapid move of China and India from low-cost producers to innovators has triggered an increasing interest in the globalization of innovation activities and more specifically, on the surge of global innovation networks (GINs). However, hitherto most of the literature is either theoretical or based on a handful of cases. We do not know what are the different forms of GINs in which firms participate, both in terms of the various degrees of globalness, innovativeness and neworkedness as well as their main characteristics. In this paper, we propose a taxonomy of global innovation networks that takes into account these different dimensions. This paper provides empirical evidence about the characteristics of the different variants of global innovation networks, observed in seven European countries as well as Brazil, China, India and South Africa. It relies on firm-level data collected through a survey in 2010 and provides for the first time a theoretical and empirical overview of the different forms of global innovation networks.
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Paper no. 2011/04
Global Innovation Networks:
towards a taxonomy
Helena Barnard (
GIBS, Pretoria University, South Africa
Cristina Chaminade (cristina.chaminade@
CIRCLE, Lund University, Sweden
This is a pre-print version of a paper that has been submitted for
publication to a journal
This version: January 2012
Centre for Innovation, Research and Competence in the Learning Economy (CIRCLE)
Lund University
P.O. Box 117, Sölvegatan 16, S-221 00 Lund, SWEDEN
ISSN 1654-3149
WP 2011/04
Global Innovation Networks: towards a taxonomy
Helena Barnard and Cristina Chaminade
The rapid move of China and India from low-cost producers to innovators has triggered an
increasing interest in the globalization of innovation activities and more specifically, the
surge of global innovation networks (GINs). However, hitherto most of the literature is either
theoretical or based on a handful of cases. We do not know what are the different forms of
GINs in which firms participate, both in terms of the various degrees of globalness,
innovativeness and networkedness, as well as other key characteristics. In this paper, we
propose a firm-based taxonomy of global innovation networks that takes into account these
different dimensions. This paper provides empirical evidence about the characteristics of the
different variants of global innovation networks, observed in five European countries as well
as Brazil, China, India and South Africa. It relies on survey-based firm-level data and
provides for the first time a theoretical and empirical overview of the different forms of global
innovation networks.
Keywords: Globalization, innovation networks, taxonomy, Europe, South Africa, Brazil,
China, India
Disclaimer: All the opinions expressed in this paper are the responsibility of the individual
author or authors and do not necessarily represent the views of other CIRCLE researchers.
Helena Barnard*
GIBS, U. Pretoria, PO Box 787602, 2146 Johannesburg, South Africa
Cristina Chaminade
CIRCLE, Lund University, PO Box 117, 22100 Lund, Sweden
Abstract: The rapid move of China and India from low-cost producers to innovators has
triggered an increasing interest in the globalization of innovation activities and more
specifically, the surge of global innovation networks (GINs). However, hitherto most of the
literature is either theoretical or based on a handful of cases. We do not know what are the
different forms of GINs in which firms participate, both in terms of the various degrees of
globalness, innovativeness and networkedness, as well as other key characteristics. In this
paper, we propose a firm-based taxonomy of global innovation networks that takes into
account these different dimensions. This paper provides empirical evidence about the
characteristics of the different variants of global innovation networks, observed in five
European countries as well as Brazil, China, India and South Africa. It relies on survey-based
firm-level data and provides for the first time a theoretical and empirical overview of the
different forms of global innovation networks.
Key words: Globalization, innovation networks, taxonomy, Europe, South Africa, Brazil,
China, India
*Corresponding author: Tel. +27 11 771 4000/4213
Email addresses:
(H. Barnard), (C.
1. Introduction
In 2006 the UNCTAD published a report on R&D Foreign Direct Investment which
pointed out, almost for the first time, to the changing role of middle-income countries in the
global flows of innovation-related investments (Unctad, 2006). It showed how R&D
investments to and from middle-income countries had increased dramatically in a few years.
Since then, a growing number of studies (e.g. Altenburg et al., 2008; Barnard, 2008;
Demirbag and Glaister, 2010; Dossani and Kenney, 2007; Ernst, 2007; Gammeltoft, 2008;
Hamilton, 2006; Huggins, 2007; Sachwald, 2008; Shi, 2007) have been trying to understand
the drivers, consequences and dynamics of the new global configuration of innovation
activities. This paper belongs to this new stream of literature.
The main conceptual issue raised by the emergence of global innovation networks
(GINs) is whether they represent a deepening of a long-standing phenomenon, or whether the
phenomenon represents the emergence of a new way of organising. On the one hand, the
constituent elements of GINs (globalness, innovativeness and networkedness) have been long
documented. On the other hand, GINs may represent an organisational form that is emerging
from a changing techno-social-economic paradigm in an era characterized by the ascent of
middle-income countries as important economic players in the global arena (Gammeltoft et
al., 2010; Ramamurti et al., 2009).
Although there is a general consensus on the international nature of innovation
(Archibugi and Iammarino, 2002; Cantwell, 2000a; Cantwell, 2000b; Narula and Zanfei,
2004) as well as its networked character (Coe et al., 2004; Coe N.M. et al., 2004; De Bresson
and Amesse, 1991; Ernst, 2002; Freeman, 1991; Nooteboom, 2003; Powell and Grodal, 2004;
Saxenian, 2002), there is little empirical work on the nature and functioning of GINs. Global
innovation networks are defined in this paper as “A globally organized web of complex
interactions between firms and non-firm organizations engaged in knowledge production
related to and resulting in innovation(Chaminade (2009), bold by the authors). The GINs
are thus defined in terms of its geographical spread (global rather than confined to the Triad),
the extent of its networks (both internal and external) and their outcome (innovation)
Hitherto, GINs (or related concepts) have been studied from a variety of disciplines,
as Borras and Lorentzen discuss in this special issue. The international business literature has
contributed to our understanding on why multinationals from developed countries locate
R&D activities abroad (Cantwell and Piscitello, 2005b; Kuemmerle, 1999; Pearce, 1999;
Rodriguez, 2011), while economic geographers and innovation scholars have highlighted the
networked character of innovation at a global scale (Coe and Bunnell, 2003; Gertler and
Levitte, 2005; Oecd, 2008; The Economist Intelligence Unit, 2007; Zander, 1999). However,
most empirical evidence is based either on a small number of qualitative case studies of large
multinational companies, on patent data (Cantwell, 2004; Cantwell and Piscitello, 2002;
Cantwell and Piscitello, 2007; Cantwell, 2000b; Federica and Zanfei, 2009; Gerybadze and
Reger, 1997) or strategic alliances by large firms (Hagedoorn, 1993; Narula and Hagedoorn,
1998; Narula and Zanfei, 2003). What emerges from the international business literature and
innovation studies is a story of the globalization of innovation driven virtually exclusively by
large multinational corporations (MNCs) with their headquarters in developed countries. The
UNCTAD report (2006) suggests that this may be changing and we may be witnessing the
emergence of other forms of global innovation networks, driven by a variety of actors (large
and small, multinational and standalone firms) from both high and middle-income
This paper links to this more recent literature by questioning if GINs are an exclusive
phenomenon of large MNCs from developed countries, as the literature may suggest. It also
The three concepts will be discusses in detail in the theoretical section
considers the degree of globalness, networkedness and innovativeness of firms in both high
and middle-income countries to map which forms of global innovation networks are
emerging. Answering these two research questions requires the collection of data that
includes both MNCs and non-MNCs, internal and external networks, small and large firms
and from high- and middle-income countries. This has not been done until now.
Using firm-level data collected through a survey in 2010 in five European countries as
well as Brazil, China, India and South Africa, this paper provides for the first time a
theoretical and empirical overview of the different forms of global innovation networks, the
role of different actors (such as MNCs and non-MNCs as well as large and small firms) in
global innovation networks and the role of high- and middle-income countries in such
We find evidence of a variety of GINs with different degrees of globalness,
innovativeness and networkedness. In contrast to the prevailing understanding of GINs, we
find that firms that are neither too large nor too small that are the ones that are engaged in
strong forms of GINs (simultaneously highly global, highly innovative and highly
networked). We also find a significant number of GINs that are formed by standalone firms,
as opposed to MNCs. All-in-all, our findings indicate that there is a much larger variety of
actors engaging in GINs than what the existing literature suggests. Levels of globalness,
innovativeness and networkedness tend to co-occur, although it is possible to have an
emphasis on one of the dimensions. For example, our evidence suggests that there seems to
be some kind of trade-off between being innovative and being global as many of the most
innovative companies are often those that keep their innovation networks at a regional or
national level.
2. Conceptual framework
The internationalization of innovation activities is not a new phenomenon. Firms have
long commercialized their new products and processes in international markets (Archibugi
and Michie, 1995; Le Bas and Sierra, 2002), have engaged in research collaboration beyond
national boundaries (Hagerdoorn, 1990; Howells, 1990) and have located R&D activities in
other countries (Cantwell and Piscitello 2005; Cantwell and Piscitello 2007; Dunning and
Lundan 2009). Typically, the internationalization of innovation activities has taken place
within the Triad – Europe, USA and Japan – and has generally involved the adaptation of
products to the local markets rather than the generation of radical new innovations abroad.
Furthermore, it has been essentially a phenomenon driven by large MNCs from developed
countries (Cantwell and Piscitello, 2005a; Cantwell and Piscitello, 2007; Dunning and
Lundan, 2009; Le Bas and Sierra, 2002; Zanfei, 2000). This MNC-centred literature has had a
strong influence on the conceptualization of global innovation networks as networks around
However, this view may be too limited. The rapid accumulation of capabilities in
certain regions in middle-income countries, the availability of qualified resources at lower
costs and the rapid development of markets in middle-income countries are facilitating the
emergence of new forms of global innovation networks rather than the one that dominates the
literature on internationalization of R&D. To the extent that globalness can be taken to mean
a geographical spread that is confined to a specific geographical area like the Triad or truly
global (Dickens, 2007), networkedness can refer to the existence of networks that are
internalized, externalized or both (Castellani and Zanfei, 2006) and innovativeness can refer
to degrees of novelty, from new to the firm to new to the world, GINs can vary according
their degrees of globalness, networkedness or innovativeness. For example, a European MNC
locating an R&D lab in another European country to adapt the product to the local market
could be a GIN that is more regional
than global, more internally networked than externally
and only incrementally innovative. On the other side of the spectrum, we may encounter a US
firm that is investing in the development of a completely new to the world bio-fuel in India
with inputs coming from a firms in China and a university in Germany, which is a GIN that is
highly global, highly networked (internalized and externalized) and highly innovative. We
therefore expect that:
H1. There are different forms of GINs according to their degree of globalness,
networkedness and innovativeness
Regarding the globalness of the phenomenon, although it is true that innovation has
been long an international phenomenon, it has hardly been a global one (Castellacci and
Archibugi, 2008). While internationalization can be conceptualized as the “simple
geographical spread of economic activities across national boundaries with low levels of
functional integration” (Dickens, 2007), globalization implies“both extensive geographical
spread and also high degree of functional integration” (op.cit: 8). The empirical evidence at
both macro (Castellacci and Archibugi, 2008) and micro level (Cantwell, 2000a; Cantwell
and Janne, 1999; Cantwell and Piscitello, 2005b; Cantwell and Santangelo, 2002; Federica
and Zanfei, 2009; Gerybadze and Reger, 1997; Narula and Zanfei, 2004) suggests that the
majority of of inbound and outbound R&D flows have traditionally taken place within the
Triad. However, this may be changing. Not only have the R&D flows to and from middle-
income countries increased substantially in the last decade (UNCTAD, 2006), but some
middle-income countries are also considered the preferred destination for the location of
R&D facilities abroad in a selected industries (The Economist Intelligence Unit, 2007). This
same accumulation of capabilities is regarded to be the main driver for the growing number
Regional meaning here supra-national regions, like the European union
of MNCs from middle-income countries that have started to locate R&D subsidiaries abroad
in the last decade (Amighini et al., 2010). Given these changes, we expect that the old focus
on high-income countries may be out of date and hypothesise:
H2. GINs are a phenomenon involving firms from middle-income countries in addition
to firms from high-income countries
Regarding networkedness, the literature on internationalization of R&D has mainly
focused on internalized networks, that is, networks of subsidiaries belonging to the same firm
that might be located in different countries and that are performing different functions
(Castellani and Zanfei, 2006). However, innovation is also the result of the continued
interactions between firms and other organizations (Freeman, 1987; Lundvall, 1992; Nelson,
1993), that is, externalized networks. Although the advanced MNCs can benefit from their
extensive networks (Andersson et al., 2002; Zhao et al., 2005), the literature on routines
(Becker, 2004) suggests a dual consequence of well-developed capabilities: Although firms
become highly competent in certain areas, their competence also remains largely limited to
those areas (Cantwell and Fai, 1999; Stuart and Podolny, 1996; Vertova, 1999). In other
words, they may also be at risk of lock-in into their current practices.
This suggests that externalized networks are also important for the emergence and
development of global innovation networks (Castellani and Zanfei, 2006), which has
important implications in terms of the type of actors that we may expect to find in GINs.
While large MNCs have the best developed internalized networks, one could expect other
forms of organization – stand-alone firms or SMEs – to be important players in the
emergence and development of GINs based on externalized networks. For example, Prahalad
(2006) offers examples of new to the world innovations that were generated outside of
middle-income countries’ MNCs, and instead originated from smaller firms or in quite a few
cases, partnerships between both firm and non-firm partners. We therefore expect that GINs
will not be the domain only of MNCs, and that different types of GINs will emerge from
different types of firms. In short:
H3a. MNCs and stand-alone firms participate in different forms of GINs
H3b. Large and small firms participate in different forms of GINs
Regarding networkedness and globalness, one of the commonly mentioned
characteristics of how middle-income countries engage in business is their use of business
groups and networks. Such networks are often argued to be a mechanism firms use to
compensate for an underdeveloped institutional context (Chang and Hong, 2002; Khanna and
Yafeh, 2007). Rather than internalise all the capabilities they need to compete effectively,
firms access the most appropriate sources of capabilities through loose networks. Because of
their previous use of business groups, firms from middle-income countries may be
particularly experienced at accessing knowledge and capabilities through networks. This
could put them at an advantage in terms of the ability to access global networks, leading us to
H4. Firms from middle-income countries rely more on global networks than firms
from high-income countries.
In terms of innovativeness, it has been generally argued that the proportion of firms
introducing innovations that are new to the firm versus new to the world varies significantly
between high-income and middle-income countries (Fifarek and Veloso, 2010). Whilst most
of the new to the world innovations are being implemented by firms headquartered in the
North, product innovations in middle-income countries are often behind the technological
frontier: it is mainly imitative innovation, more related to the acquisition of technology
developed somewhere else and its adaptation to the local needs rather than to the
development of new products (Bell and Pavitt, 1993, 1995; Coe and Bunnell, 2003; Edquist,
2005). Following the logic expressed in this literature, we might expect that new to the world
innovation will continue to take place in networks dominated by multinationals from high-
income countries while firms in low and middle-income countries will use their innovation
networks to acquire existing technology that will be further introduced to the firm. Therefore
we expect that:
H5. Global networks in which firms from middle-income countriesparticipate mainly
involve incremental innovations.
3. Methodological design
3.1. Ingineus survey and data base
This research project relies on a survey conducted across nine countries under the auspices of
the EU-funded INGINEUS project. Data on firms in Europe were gathered from leading
economies with a per capita income above US$ 45 000 per year, namely Denmark, Germany,
Norwayand Sweden. Estonia, a transition economy was also polled
, as well as four
prominent middle-income countries: Brazil, China, India and South Africa. The choice of
countries allows a clear comparison between economies that are global leaders and ones that
are largely followers in the global arena.
The survey for each country focused on either ICT, automotive or agro-processing
whichever sector was of economic importance in that country. The sectors were chosen to
represent an old industry with low research intensity (agro-processing), a more established
Estonia is an unusual case, based in Europe but with a similar level of development as the middle-income
countries. It contributes only 17 out of 1215 data points, and does not meaningfully affect the results.
Sweden had both auto and ICT surveys.
industry with a medium level of research intensity (automotive) and a young, highly research-
intensive industry (ICT)
Because one of the goals of the INGINEUS project was to extend insights about GINs
beyond large multinationals from high-income countries, the choice of datasets was
complicated. Where possible, a sample frame was established by using existing databases,
e.g. Statistics Sweden or the German commercial database Hoppenstedt. This was not always
possible, especially for the middle-income countries. There the strategy was to combine
existing (but often out-of-date or inadequate) databases, e.g. in Brazil the database of the
automotive union SINDIPECAS, the official Annual Registry of Social Information (RAIS) and
information from large automotive firms about their suppliers was used to compile a sample
. All databases were filtered to ensure that firms with five or more employees were
Table 1: Survey results by country and industry (number of responses; response
rates in brackets)
Countries ICT Auto Agro TOTAL
Brazil 69
China 243 (2.7%)
Estonia 17 (14%)
India 324 (20.2%)
South Africa 84 (16.9%)
TOTAL middle-income
584 (5.34%) 69 (25.9%) 84 (16.9%) 737 (6.32%)
Denmark 49 (23.3%)
Germany 53 (4.7%)
Norway 181 (11.9%)
Sweden 171 (10.3%) 24 (14.3%)
TOTAL high-income
352 (11.05%) 77 (6.18%) 49 (23.2%) 478 (10.59%)
Total 936 (6.59%) 146 (10.64%) 133 (18.58%) 1215 (7.5%)
One of the insights from the survey, not the focus of this paper, is that the supply chain has fragmented to the
extent that there are more and less research intensive activities in any given industry. This raises important
questions about industry selection for future studies.
See (accessed Dec 1, 2011)
for more detail about the data gathering process.
The information gathering also took place in a variety of different ways. In countries
with a culture of participating in surveys, e.g. the Scandinavian countries, firms were sent a link
to an online tool. In the middle-income countries, data gathering was done best telephonically or
through face-to-face interviews. In all sectors and across all countries 1215 responses were
Table 1 offers a summary of the results received from each sector and each country,
the number of responses and response rates. The combined INGINEUS sample was
dominated by ICT responses. This is in part due to the size of India and China, but also due to
the more established and thus concentrated nature of the agro-processing and auto industries.
Although China has the second-highest number of responses, it also has the lowest response
rate (2.7%). This is because the Chinese team had opted to choose a broader sample and use a
less labour-intensive strategy for targeting respondents. The low German response rate is
most likely due to the fact that the questionnaire was sent out during a period when the
German automotive industry was struggling with the aftermath of the economic crisis.
However, the most important driver of response rate is probably the initial
methodological decision to define possible participants for the survey very broadly. This may
have resulted in both a somewhat lower and a somewhat biased sample
. For example, the
smaller firms included in the survey are more likely those with a somewhat greater
international orientation. Although care should therefore be taken in generalising findings,
the large number of responses provides confidence that the patterns uncovered are not
spurious. In addition, the more inclusive approach allows us to map how smaller firms,
standalone firms, and firms located in middle-income countries – previously largely ignored
economic actors – participate in GINs.
For example, some smaller firms declined to participate on the basis of either limited human resources or because they saw
themselves as locally rather than globally networked.
3.2. Analysis of global innovation networks
For each of the three concepts (Global, Innovative and Networked), relevant questions in the
survey were chosen and then weighted according to their importance. The precise wording of
all questions is included as an Annex to this paper. A scoring system was devised, and a
formula specified which gave each instance in the dataset a continuous value greater than or
equal to 0. This value was divided by the maximum value in the dataset, so that each instance
had a continuous score between 0 and 1, with the instance with score 1 being that which most
epitomised the concept in question. This resulted in each instance being scored relative to the
other instances in the dataset.
These scores were displayed on a scatter plot, and a combination of cluster analysis
and inspection of the scatter plot used to identify the cut-off point between categories, e.g.
highly global, somewhat global and not at all global. Alternative scoring systems were
explored to test the robustness of the original scoring. Once the scoring was determined, each
instance in the dataset was classified as one of the types of GINs.
3.2.1. Globalness
The purpose of this measure is to establish the degree of globalness (rather than
innovativeness or networkedness), and it was therefore deemed important to not give greater
weight to more “complex” activities (like innovation) than to “simpler” tasks like exports –
what matters is global reach. We therefore considered all questions that asked respondents
about the locational spread of their activities, regardless of what those activities were.
For indications of Globalness, we used several indicators like the percentage of total
sales derived from exports, firms’ largest markets, the geographical location of partners with
whom firms collaborate for innovation, the location of the different functions of the firm (by
the unit in location, by geographically dispersed subsidiaries or outsourced) and the location
of firms’ outsourced or offshored production or innovation activities (if they do use
After transforming each value so that they all had a score between 0 and 1, all five
categories listed in the table were used to calculate an average. For the robustness test an
average was calculated where questions 4.2 (regarding sales) and 7 (regarding innovation)
were given greater weight. Those questions are more fine-grained and force the respondent to
state precisely which regions are involved.
We use k-means cluster analysis with two groups and the squared Euclidean distance
as the distance measure between points. The silhouette plot for the analysis where greater
geographical distance has greater value is shown below. The diamond markers indicate
Cluster 1 and the circle markers indicate Cluster 2. The mean of Cluster 1 is 0.5178 and the
mean of Cluster 2 is 0.0552. Looking at the scatter plot, the value 0.283 is a natural break
point and we classify all instances >0.283 as G (highly global), all instances greater than 0
and up to 0.283 as g (somewhat global), and all instances of zero as *.
Figure 1: Distribution of values for globalness using equal weights
A similar process for the model where all instances of globalness are given equal
values results in a cut-off point for >0.27 as G, and for all instances greater than 0 and up to
0.27 as g.
Comparing the two models, we observe that these two formulae (based on different
questions) give similar groupings. Numerically, 99.09% of all 1215 instances in the dataset
have the same value under each of the models. This implies that the scoring system for
globalness is robust.
Figure 2: Robustness check of two models for globalness
3.2.2. Innovativeness
With regards to innovation, respondents were asked to indicate if they have innovated in
2006 to 2008 in any of five categories: New products, new services, new or significantly
improved methods of manufacturing or producing, new or significantly improved logistics,
distribution or delivery methods for your inputs, goods and services and new or significantly
improved supporting activities for your processes (e.g. purchasing, accounting, maintenance
systems, etc.). For each of the options selected, the respondent was asked to indicate if the
innovation was new to the world (which was given a value of 3), new to the industry (with a
value of 2) or new to the firm (with a value of 1). This yielded a maximum score of 15.
However, that scoring system implies that there is a linear progression from new-to-the-firm
to new-to-the-industry to new-to-the-world innovations, whereas it may be significantly more
complex to generate more novel innovations. To test for robustness, all scores for “new to the
world” were multiplied by 3 (to a maximum of 9), and all scores for “new to the industry” by
2 (to a maximum of 4). This approach provides greater weighting by degree of
We first do a cluster analysis using the linear scale. The diamond markers indicate in
Figure 3 indicate Cluster 1 and the circle markers indicate Cluster 2. There seems to be a
break at around 0.7. However, this is a very strict cut-off point, as less than 2% of the values
fall above this point. Therefore, we choose the next most obvious cut-off point (by
inspection), which is just below 0.6. The values get much denser below this point, and
increasingly sparser above this point. We classify all instances >=0.6 as I (highly innovative,
all instances between 0 and 0.6 as i, and zero as *.
Figure 3: Distribution of values for innovativeness using linear scale
To test the robustness of the cluster analysis, we do a similar analysis, but one where
innovations are given much greater weightings for greater novelty. The graphical
representation of the comparison indicates that although the two sets of markers are not one
on top of the other, they follow the same general trends. Since the y-axis denotes the instance
number, it is clear that many of the same instances occur for the two formulae, although the
ordering may be slightly different (as each formula has a slightly different number of
instances classified as “I”). In other words, since the markers for both scores appear on the
same horizontal gridlines, the two scoring systems must classify most of the instances in the
same way. Doing a logical check, we find that 95.72% of the values for the two scores are
identical. This suggests that the scoring system for innovativeness is robust.
Figure 4: Robustness check of two models of innovativeness
3.2.3. Networkedness
In operationalizing the concept of networkedness, we considered debates about the indicators
of a “strong” network. Formal linkages may be seen as especially strong, as they provide the
benefit of legal protection (Li et al., 2010). However, there is also an argument that trust may
be reduced by formal control mechanisms (Das and Teng, 1998; Malhotra and Murnighan,
2002) and that informal linkages may signal especially strong relationships. Similarly,
although it is plausible that the strongest network would be within the firm – where people
share an organisational culture and goal – it is also possible that a firm may be less inclined to
take for granted and therefore take more care to nurture important external networks. This
point also relates to our argument that effective networks are possible not only among
multinationals, but also among standalone firms that cultivate strong external networks.
We therefore incorporate two measures of connectedness, span and depth. An
enterprise is highly networked firstly if it has connections or relationships with many other
people, enterprises or institutions. The more connections which an enterprise has with people
or bodies outside of the enterprise itself (e.g. clients, suppliers, competitors, universities,
etc.), the larger is the span of the network. Secondly, an enterprise is highly networked if
those connections or relationships are deep. A deep connection is one which is meaningful or
even crucial to the running, development or success of the enterprise.
In developing the measures, we considered both internal/external (to capture span)
and formal/informal linkages (to capture depth). We calculate three scores for networkedness,
one where all scores are given equal weighting, one where external linkages are given greater
weight than internal linkages, and one where formal linkages are given greater weight than
informal linkages.
Networkedness was based on the following questions: How different functions of the
firm are performed (by the unit in location, by subsidiaries or outsourced), with whom
outside the firm it has been collaborating for the development of its most important recent
innovation, and whether a firm has developed formal/informal linkages (e.g. research
relationships) with a variety of external organizations, e.g. universities, research institutes,
government etc.
Figure 5 maps values for networkedness with an equal weight for all indicators. The
diamond markers represent Cluster 1 and the round markers represent Cluster 2. Although the
figure indicates that the two clusters are separated around 0.2, the data points at the break for
clusters 1 and 2 are very close together – almost on top of each other. At the same time, the
above plot shows a slight gap in data values around 0.4. Looking at the scatter plot, this
seems to be closer to where the natural break occurs. Therefore we reject this cluster analysis,
and rely instead on inspection of the scatter plot in order to decide on a natural break in the
data values. Taking into account that the percentage of values greater than 0.2 = 15.3909%,
greater than 0.28 = 8.9712%, greater than 0.32 = 6.6667% and greater than 0.4 = 3.7860%,
we consider a natural break at 0.32 (by inspection). Following this model, we classify all
instances >0.32 as N (highly networked), all instances with a value greater than 0 and as high
as 0.32 as n (somewhat networked), and all instances of zero as *.
Figure 5: Networkedness using equal weights
The second and third models emphasize the relative formality of linkages, and
external scope of linkages respectively. Each time, using the same process described before,
it is calculated which respondents can be considered highly networked, somewhat networked,
and not at all networked.
Figure 6 compares the three models. In most instances, the same value is obtained
regardless of which model us used. Numerically, 97.2% of all 1215 instances in the dataset
have the same scoring for networkedness. This implies that the scoring system is robust.
Figure 6: Robustness of scoring for networkedness.
4. Results – Towards a firm-based taxonomy of GINs
The fact that the indicators for globalness, innovativeness and networkedness proved to be
robust to different operationalisations of each construct suggests that they tap into robust
Using the calculated scores, we classify each firm within one of the types of global
innovation networks. We use a capital letter to indicate that the firm is highly global (G),
highly innovative (I) or highly networked (N), and small letters if the firm has been classified
as somewhat global (g), somewhat innovative (i) or somewhat networked (n). Finally, we use
an asterisk (*) in cases where a firm is not at all global, innovative or networked.
Mathematically, twenty-seven (3x3x3) permutations are possible, but to the extent that firms
are engaging in some form of GIN not on a random basis, but because of an underlying logic,
we expect that only some combinations will be seen.
The results indicate that there is an underlying logic for firms’ behaviour. Certain
combinations are not found – it is extremely rare to find a firm scoring highly on one
dimension, and not at all on another dimension.
In fact, only twelve of the possible 27
categories account for more than 97% of the dataset, and it is possible to combine those
twelve categories into six main types. In addition, there are indeed some strong-form GINs –
firms that are highly global, highly innovative and highly networked. They represent only 15
firms (just more than 1%) in the sample, but given the emergent nature of the phenomenon,
this is to be expected. The types are presented in Table 2. The strong-form GINs are
discussed in more detail later.
The results provide support for our first hypothesis H1 that there are different forms
of GINs.
Table 2: Firm-based taxonomy of GINs
Type of GIN Description Values
Forms of GINs
Balanced GINs
All elements are in alignment GIN (1.23% of
gin (40.41%)
*** (12.18%)
Global asset exploiters Global reach is greater than the extent
of innovation or networkedness
Gin (2.96%)
g** (1.65%)
Firms are relatively more innovative
than their global reach or the extent of
their networks would suggest
gIn (2.63%)
*i* (1.89%)
Strength of networks is greater than
global reach or innovativeness
giN (1.48%)
**n (5.76%)
Global networkers
Innovation is not as high as both the
globalness and the networkedness. This
is the only common combination of two
stronger dimensions
GiN (4.36%)
g*n (3.79%)
Domestics Firms that have no supra-national
footprint at all, but are innovative and
networked enough to (presumably)
survive domestically or locally – this
category accounts for the second
largest group of firms.
*in (18.93%)
In terms of how we designate types, it virtually never happens that a firm would be described with both an
asterisk and a capital letter.
The greatest proportion of firms, 40% of the sample, consists of firms that are
somewhat global, somewhat innovative and somewhat networked, and the third most
commonly found category (12% of the sample) of firms that are not at all global, innovative
or networked. These firms are all “balanced”, in that their globalness, innovativeness and
networkedness are at an equal level of development. The prevalence of cases where the three
elements are at a similar level of development suggests that there is indeed an element of
co-evolution in their development.
Almost a fifth of the dataset (the second-largest category overall) consists of firms
that have no supra-national connection at all, but are still somewhat innovative and
networked. These firms are clearly focused on a domestic market. But the evidence of the
power of globalization is clear from the fact that for the categories of global asset exploiters,
innovators and global networkers, there are fewer the firms that are somewhat global,
innovative and globally networked than firms with high scores on those dimensions.
Figure 7. Distribution of stronger forms of GINs
Mapping the entire dataset is useful in order to quantify the relative importance of
GINs, and it provides evidence that close to 15% of the firms in the dataset are highly global,
innovative and/or networked. These firms belong to various stronger forms of GINs, and it is
worth investigating the characteristics of the stronger forms GINs.
4.2. Characteristics of the stronger forms of GINs
Table 3 provides evidence of some core characteristics of the stronger forms of GINs, that is,
those that have a higher degree of globalness, networkedness or innovativeness. It also allows
us to discuss hypothesis 2 (on the importance of middle-income country firms in GINs), 3a
and 3b (on the importance of other types of actors rather than only large MNCs), and
hypotheses 4 and 5 (on the types of GINs that are more common for firms in middle-income
countries). Table 5 summarizes the main characteristics of the different forms of GINs in
terms of location (H2), type of actor and size (H3).
The Global asset exploiters and global networkers have a similar distribution in
terms of both size (large firms) and firm type – they are mainly the subsidiaries and
headquarters of MNCs. Among the global asset exploiters, the European locations are
relatively well represented. These firms seem to follow a fairly traditional model of market-
seeking expansion.
In contrast, the Global networkers is the single category where middle-income
country firms are most prevalent – with almost 7% of all respondents located in middle-
income countries in the dataset represented in this category. Networkers are also large firms,
also predominantly subsidiaries and headquarters of MNCs, but firms from middle-income
countries are not as readily found as among the global networker category.
The comparison between Networkers and global networkers is useful because the
main dimension of difference is the scope of the network. It is telling that the firms located in
middle-income countries are so much more global, and that high levels of globalness and
networkedness co-occur, but not innovativeness. This pattern is consistent with previous
evidence about the relatively lower innovativeness of middle-income country firms. We
suggest that the less munificent institutional context of entities in less developed countries is
an important explanatory factor in their strong drive for global networking.
In contrast, Innovators are more often from Europe than any other category, more
often small (less than 50 employees) standalone firms, and more likely to generate new to the
world product and/or service innovations than any other category. It seems that these players
are most able to draw on an appropriate regional institutional infrastructure. Innovators are
relatively small firms that offer new-to-the-world goods and services. Previous research has
suggested that new-to-the-world innovations are especially critical to an economy, and
therefore these firms have the potential to play a particularly important role in an economy.
However, Innovators have a very low proportion of exports and few international clients.
This raises the question of whether firms are capturing adequate economic value from their
innovations –it seems likely that more markets could be found for their innovations.
It is worth to look in detail at those firms that are highly global, highly innovative and
highly networked (GINs with block capitals) within the Balanced GINs – we call these the
strong-form balanced GINs . Of the fifteen firms that fall in this category two are in the
agro-processing industry, and the other thirteen all in ICT. This to some effect reflects the
dominance of ICT in the dataset, although this result is also quite consistent with the
literature that has long argued that globalization is more likely to occur in some industries
than in others, due to the different nature of their knowledge bases (Asheim and Gertler,
2005; Pavitt, 1984). The fact that no automotive firms are part of strong-formbalanced
GINsis also consistent with the fact that the automotive industry is divided into first, second
and third tier suppliers, suggesting a value chain rather than a looser network.
Table 3: Characteristics of firms participating in stronger form GINs
% of all firms in
that industry
% of all firms in that
country (number)
% of all firms of that
size (number)
Firm type
% of all firms of that firm
type (number)
Location responding unit
% of all firms of that type in
that location (number)
Global asset
38 cases, 3.13%
of dataset
Auto 2.05% (3)
Agro 1.50% (2)
ICT 3.53% (33)
China 0.82% (2)
India 8.02% (26)
South Africa 1.19% (1)
Middle-income 4.03% (29)
Denmark 2.04% (1)
Germany 3.77% (2)
Norway 1.66% (3)
Sweden 1.54% (3)
High-income 1.82% (9)
<10 1.53% (2)
<50 1.94% (7)
<250 4.39% (13)
<1000 4.71% (8)
>1000 6.80% (7)
No info 0.65% (1)
Standalone 2.31% (16)
Subsidiary 6.50% (16)
MNC HQ 4.44% (6)
Middle-income 2.98% (10)
High-income 1.83% (6)
Middle-income 7.61% (15)
High-income 1.79% (1)
Middle-income 3.39% (4)
High-income 11.11% (2)
53 cases, 4.36%
of dataset
Auto 2.05% (3)
Agro 3.01% (4)
ICT 4.91% (46)
Brazil 2.90% (2)
India 13.89% (45)
South Africa 3.57% (3)
Middle-income 6.94% (50)
Germany 3.77% (2)
Sweden 0.51% (1)
High-income 0.61% (3)
<10 0.76% (1)
<50 0.83% (3)
<250 4.73% (14)
<1000 10.59% (18)
>1000 16.50% (17)
Standalone 1.59% (11)
Subsidiary 9.76% (24)
MNC HQ 13.33% (18)
Middle-income 2.68% (9)
High-income 0.61% (2)
Middle-income 12.18% (24)
High-income 0.00% (0)
Middle-income 14.41% (17)
High-income 5.56% (1)
20 cases, 1.65%
of dataset
Auto 1.37% (2)
Agro 2.26% (3)
ICT 1.60% (15)
India 3.09% (10)
South Africa 3.57% (3)
Middle-income 2.29% (13)
Germany 3.77% (2)
Sweden 2.56% (5)
High-income 1.41% (7)
<10 0.76% (1)
<50 1.11% (4)
<250 1.69% (5)
<1000 1.76% (3)
>1000 4.85% (5)
No info 1.30% (2)
Standalone 1.01% (7)
Subsidiary 3.25% (8)
MNC HQ 2.96% (4)
No info 1
Middle-income 0.60% (2)
High-income 1.52% (5)
Middle-income 3.55% (7)
High-income 1.79% (1)
Middle-income 3.39% (4)
High-income 0.00% (0)
36 cases, 2.96%
of dataset
Auto 0.53% (5)
Agro 1.50% (2)
ICT 3.10% (29)
Brazil 5.80% (4)
China 1.23% (3)
India 5.25% (17)
South Africa 1.19% (1)
Middle-income 3.47% (25)
Denmark 2.04% (1)
<10 0.76% (1)
<50 3.60% (13)
<250 4.39% (13)
<1000 2.94% (5)
>1000 3.88% (4)
Standalone 2.89% (20)
Subsidiary 4.07% (10)
MNC HQ 3.70% (5)
Middle-income 3.57% (12)
High-income 2.44% (8)
Middle-income 4.06% (8)
High-income 3.57% (2)
Middle-income 3.39% (4)
High-income 5.56% (1)
% of all firms in
that industry
% of all firms in that
country (number)
% of all firms of that
size (number)
Firm type
% of all firms of that firm
type (number)
Location responding unit
% of all firms of that type in
that location (number)
Norway 2.76% (5)
Sweden 2.56% (5)
High-income 2.22% (11)
No info 1
balanced GINs
15 cases, 1.23%
of dataset
Auto 0 % (0)
Agro 1.50% (2)
ICT 1.39% (13)
China 0.41% (1)
India 3.40% (11)
South Africa 2.38% (2)
Middle-income 1.94% (14)
Norway 0.55% (1)
High-income 0.20% (1)
<10 0.76% (1)
<50 0.00% (0)
<250 1.35% (4)
<1000 4.12% (7)
>1000 2.91% (3)
Standalone 0.58% (4)
Subsidiary 4.07% (10)
MNC HQ 0.74% (1)
Middle-income 0.89% (3)
High-income 0.30% (1)
Middle-income 10.71% (10)
High-income 0 (0)
Middle-income 0.84% (1)
High-income 0 (0)
As regards the size distribution of the strong form Balanced GINs, one very small
firm is found, and the others range in size from between 50 and 1000 employees. This is
smaller than would be the case for most traditional industries (e.g. much of manufacturing),
and suggests that there may be a current optimal point in terms of number of employees as
regards the complexity of managing a GIN. Those firms with a global footprint (global asset
exploiters and global networkers) that are only somewhat innovative are generally large firms
with 1000 plus employees, and those firms that are highly innovative but with a limited global
footprint tend to be very small (around 50 employees). In contrast, the strong form balanced
GINs have a considerable footprint, although they have clearly not internalised all activities.
This could also be related to the fact that the majority of those firms are in ICT, which may
particularly well lend itself to externalised rather than internalised networks with a stronger
skills than labour component and often fewer in-house employees.
The location of the strong form balanced GINsis somewhat surprising in relation to
what we might expect from the existing literature. One such GIN is found in China, two in
South Africa, and eleven in India. In India, five of them are the subsidiaries of advanced (and
in fact, US) MNCs, as is the single Chinese strong form balanced GIN. But an additional five
of the strong form balanced GINs are subsidiaries or headquarters of emerging MNCs, and
four more are stand-alone firms. Apart from the Norwegian firm, the only European
participation in this list is the fact that two of the emerging MNCs whose subsidiaries are
represented have dual headquarters, both in their country of origin and in a European country.
The evidence suggests that it would be wrong to regard strong form balanced GINs as
the domain primarily of the most advanced MNCs of high-income countries. Strong form
balanced forms of GINs seem to have two origins: Some are advanced MNCs from high-
income countries who are organizing their operations into GINs, who are able to manage the
complexity of a global network and achieve substantial innovation, also when they locate in
and draw on the resources of less developed countries. The other strand of strong form GINs
is made up from firms in middle-income countries that have long had global networks, but are
also achieving notable innovation.
When all the five forms of GINs are considered, one can clearly see that GINs are no
longer a phenomenon of firms from high-income countries (H2) but not all middle-income
countries considered in the analysis show a deep embeddedness in GINs. As can be seen from
Table 4, GINs also seem to a certain extent to be an “India” phenomenon with a third of the
Indian dataset showing up as a strong form G, I and/or N. Part of the reason may be that the
India survey was conducted in the ICT sector with its emphasis on connectedness, and the
virtual (and therefore easily globalised) nature of many of its offering. However, countries
like China and Norway also conducted the survey in ICT, and do not seem to have so many
GINs. This indicates that firm strategy matters: India is English-speaking, it is a popular
outsourcing destination for established MNCs, and domestic Indian firms often target the
global market first. In contrast, China and Norway experience not only language barriers, but
there is also a stronger domestic focus among IT firms.
Table 4: Participation in some stronger-form GIN
Respondents participating in a stronger form GIN #
% of all respondents
from that country
Brazil 6 8.70%
China 6 2.47%
Estonia 0 0.00%
India 109 33.64%
South Africa 5 5.95%
Total middle-income countries 126
Denmark 2 4.08%
Germany 6 11.32%
Norway 9 4.97%
Sweden 14 7.18%
Total high-income countries 31
Although the analysis of the strong form balanced GINs provides evidence supporting
hypothesis 4, as Table 4 shows, there are only small differences in the percentages of firms
from high-income and middle-income countries that participate in strong forms of GINs in
general. Therefore, we can only accept partially hypothesis 4.
As regards to the characteristics of the firms engaged in different forms of GINs, our
results provide support for hypothesis H3a and H3b (that both MNCs and stand-alone firms,
as well as both large and small firms participate in different forms of GINs). MNCs are
predominant among the global asset exploiters, networkers and global networkers, but many
stand-alone companies are classified as global asset exploiters and global networkers. GINs
are not any longer a phenomenon exclusively of large firms, as small and medium size firms
are often found among especially innovators and strong form balanced GINs.
Table 5: Main characteristics of different forms of GINs according to origin, type and
size of the firm
Bigenoughtohandleinternat ionalizationwithoutlosingcapacity
Finally, it is interesting to see that in terms of industry, the auto industry has a strong showing
in two categories – innovators and global networkers, although it does not have any strong
form balanced GIN. The fact that firms seem capable either of strong innovation, or of global
networking, suggests that there may be some trade-off between managing advanced
innovation, and managing extensive global networks. In addition, it seems that there are
“assembler firms” in the industry that are tasked with global sourcing and integration of
innovations that come from specialist innovative suppliers, and this most likely links to
different positions in the value chain. Although the agro-processing industry does not show
up as dominant in any of the categories, it is present in the strong form Balanced GINs,
suggesting that certain types of activities may not only lend themselves to innovation, but
specifically innovation through the tapping of global networks.
4.3. Methodological limitations
It is important to note that although the paper theorises global innovation networks, what is
polled is not the network, but a single node of the network. The evidence is best described as
an “ego network”, and it suffers from the typical shortcomings of ego networks. The evidence
is self-reported, and respondents are likely to provide more accurate information on local
matters (e.g. the number of people employed at that unit) than on more distant matters (e.g.
the size of the organisation overall).
Another issue of concern is ownership and control. First, although the data provide the
location of the unit, which is adequate for standalone firms, it provides inadequate
information about the location of the parent of subsidiaries. Although post-hoc information
gathering was conducted to establish the location of the parent, this oversight is regrettable.
Specifically related to the strong representation of firms from middle-income
countries, the evidence does not allow us to adequately distinguish between a subsidiary
which is part of a strong-form GIN because it is part of the complex network of an advanced
MNC and a subsidiary that creates and uses a strong-form GIN to compensate for not only a
weaker institutional context, but also the absence of the advanced MNC’s rich network.
Stated differently, if participation in a stronger form GIN can be regarded as a form of created
asset seeking, it is not possible to establish whether the motive lies with the unit in the
responding location or with the parent. This is particularly consequential because this is a
cross-sectional questionnaire, and because firm motives evolve. We can map a certain
configuration of GINs at this point in time, but the relative importance of different firm types,
sizes of firms and locations of units is likely to change over time. This paper therefore reveals
evidence about GINs at a fairly early point of their evolution.
The constructs of networkedness and innovativeness can also be interpreted in
alternative ways. In their study of business ties in Argentina, Mc Dermott and Corredoira
(2009) point out that the number of links do not necessarily translate into the value of those
ties. It cannot be ruled out that firms from high-income countries may have fewer ties but
have learnt to use them more strategically than firms from high-income countries. Similarly,
when assessing the novelty of a given innovation, an entity in the less developed world may
judge it relative to other innovations in its less developed context, and judge it as more
innovative than an entity in Europe would, since new-to-the-world innovations are more
common there.
This shortcoming relates to the substantial challenges of conducting and interpreting a
standardised survey across very different countries and industries. In spite of considerable
efforts to ensure concordance between different countries and different industries, there are
considerable differences in the types of databases used and response rates between countries.
At a conceptual level, it must be asked to what extent even “objective” measures like the
number of people working in a firm in two contexts as different as, for example, Denmark and
India, can be regarded as comparable.
This is especially consequential because the analysis relies on relative measures for
the construction of groups. The highly globalised, innovative and/or networked respondents
are so relative to the other responses in the dataset, not according to some objective external
measure. A relative measure is useful in the case of an emerging phenomenon such as GINs,
as it allows us to capture the patterns that already exist. However, it also makes the
conclusions vulnerable to the specifics of a dataset. We believe that the size and breadth of
the dataset mitigate that limitation in this case.
Finally, it is important to remember that especially the final list of strong-form GINs is
a short one, and that the limited data allow only tentative conclusions. For example, a more
balanced dataset may or may not reveal fewer GINs in the ICT sector. The current era is
dominated by the emergence of ICT, and the ICT industry has been described as a “carrier
branch” in the overall economy (Cantwell, 2001). It may be that ICT firms lend themselves to
operating in a global innovation network. However the relatively strong showing of agro-
processing firms (2 out of a total of 133 agro-processing responses compared to the 13 out of
936 ICT responses) suggests that GINs may actually function across a range of industries.
Further research is needed to clarify the link between the nature of the industry and GIN
4. Discussion and conclusions
The firm-based taxonomy of GINs proposed in this paper challenges some of the assumptions
in the literature and opens up several avenues for future research. The research complements
the hitherto MNC-centred literature on the internationalization of innovation, and suggests
that the focus on MNCs as the sole drivers of GINs is too limited. Instead, GINs seem to
serve two main purposes: one purpose, found among the leading MNCs, is that GINs may act
as a way to accelerate innovation, complementing existing research at the headquaters (see
Castellani in this issue). The other purpose is as a compensatory mechanism when firms have
limited resources. While the bulk of stronger forms of GINs are in MNCs from the leading
economies, and there is a considerable body of work to support the importance of the MNC as
a vehicle for cross-border networks, there is a strong showing of stand-alone firms. This is not
the first evidence of the internationalisation of non-MNCs: The work on “born globals”
(Knight and Cavusgil, 2004) and work arguing that SMEs can benefit from outsourcing (Di
Gregorio et al., 2008), both indicate that smaller and stand-alone firms can form global
networks. The interviews we conducted with stand-alone companies also suggest that those
firms outsource not only tasks that are easily routinised, but also rely on partners for
capabilities that are especially complex and only occasionally needed. To the extent that non-
MNCs use global networks to compensate for limited in-house capabilities, GINs function not
as a way to accelerate innovation, but rather as a way to “level the playing field”.
The number of emerging MNCs operating within a strong form balanced global
innovation network and the dominance of firms located in middle-income countries in this
form of GINs is another robust result of this analysis, and supports the notion of GINs as a
compensatory mechanism. Our evidence suggests that firms who are institutionally somewhat
disadvantaged, or even only geographically at some distance from the leading economic
actors, have started to exploit the potential of leveraging rich and globally dispersed networks.
It is useful to consider not only the strong form balanced GINs, but the much larger list
of different types of strong GINs. By far the greatest proportion of the dataset (54%) consists
of firms where globalness, innovativeness and networkedness are in balance. But much can be
learnt from the other types of firms. Innovators (those firms scoring lower on networkedness
and globalness) are often European standalone and small firms (50 people or less) that rely
often on a limited network of partners for innovation, and mostly interact at regional or
domestic level. On the other hand, the networkers and global networkers are generally firms
with more than 1000 employees. Those firms that balance being highly innovative with
participation in global networks (strong form balanced GINs) are mostly firms with between
250 and 1000 employees.
This suggests that there is a current optimal point in terms of the number of employees
for managing and extracting value from a GIN. Engaging in global networks is costly – firms
need to develop strategies and protocols to communicate and coordinate as complex and fluid
an activity as innovation across multiple boundaries. It stands to reason that firms will only
engage in GINs if the cost of global sourcing is lower and benefits greater than finding the
resources needed for innovation locally. This can happen when firms are especially
innovative and used to operating through a complex network (the well-documented case of
the established MNCs from advanced economies), or as a compensation mechanism of firms
from a somewhat disadvantaged context.
Indeed, firms from middle-income countries may have developed the capabilities to
participate in stronger form GINs in response to institutional voids. Firms in a scarce skills
context are forced to outsource extensively, including to partners from distant locations (if
they are geographically at a distance from leading service providers). Many of the firms using
GINs as a compensatory mechanism are also used to operating through business networks in
order to overcome institutional voids (see Chaminade and Plechero in this same issue).
This suggests that operating within a GIN may not be a preference, but rather (and
perhaps increasingly) a key mode of organising activities. At the moment it seems that
especially Indian ICT entities are exploiting the opportunities of a global innovation network,
and it remains to be seen to what extent firms from other less and more developed contexts
will follow suit. Furthermore, what our results seem to suggest is that a larger geographical
spread of the network may have a negative impact on the technological advantage of the firm.
For policymakers, the core insight of this study is that GINs weaken the link between
the munificence of a location and the strength of firms from that location. Because firms can
access the most appropriate capabilities and resources wherever in the world they are found, it
is possible for “strong” firms to emerge from “weak” locations. This has different
implications for policy makers in more versus less developed countries.
In middle-income countries, participation in global innovations networks allows
world-leading firms to emerge (see Barnard, Kalvet and Tiits in this volume). But because
they can and do source so many of their needed capabilities from abroad, firms are only
loosely connected to their home location and policymakers need to develop strategies to
ensure that firms remain locally connected. This includes conducting additional research to
establish in which ways their home location can benefit from firms engaged in global
innovation networks, while still giving them the freedom to source capabilities from the most
appropriate context.
In contrast, although high-income countries often house firms from other locations,
their home-grown firms are almost paradoxically less globally connected. Supported by a
well-developed institutional infrastructure, the European firms seem to have a regional or
domestic (rather than global) focus, and (perhaps as a consequence) a limited span of
networks. While this seems to be positive for innovation at the moment, too much focus on
regional networks can lead to lock-ins and loss of competitiveness in the long term. Because
of the co-occurrence of innovation with globalness and networkedness, this trend could even
limit their longer-term innovativeness. It is therefore important to identify the triggers that
challenge firms to engage in global innovation networks.
Finally, it is important to note that global innovation networks are a rather new
phenomenon that is changing very rapidly. As regions in middle-income countries accumulate
innovation capabilities, we may witness, for example, a decrease in the need to connect
globally and a gradual turn toward less networked, less global but more innovative GINs
originating from those countries. Or we may witness a fundamental change in the way firms
are organised, comparable to the emergence of the multidivisional firm documented by
(Chandler, 1962). Ongoing research on a global scale is needed to track how this
organisational form evolves.
Acknowledgements: Research for this paper was partially funded by the European
Community's Seventh Framework Programme (Project INGINEUS, Grant Agreement
). The authors alone are responsible for its contents which do
not necessarily reflect the views or opinions of the European Commission, nor is the
European Commission responsible for any use that might be made of the information
appearing herein. Additionally, financial support from the Swedish Research Council
(Linneaus grant) is acknowledged. We are grateful to the comments received by the
participants of the INGINEUS Copenhagen workshop to an earlier version of this paper. The
usual disclaimer applies.
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ANNEX A – relevant questions from questionnaire
3.1 Does your enterprise have a significant share of sales activity abroad?
If you answered ‘Yes’ to the question above then please provide the percentage (%) of total sales derived from
4.2 If an export market was selected, then please indicate the three most important destinations in
terms of sales.
4.2.1 North America
4.2.2 South America
4.2.3 Western Europe
4.2.4 Central and Eastern Europe
4.2.5 Africa
4.2.6 Japan & Australasia
4.2.7 Rest of Asia
4.2.8 The rest of the world (developing)
8. Has your enterprise developed formal/informal linkages (e.g. research relationships) with the
following kinds of foreign organizations? (Informal implies no written contract or financial obligation
Please tick all relevant boxes.
Yes, informal No
8.1 Clients
8.2 Suppliers
8.3 Competitors
8.4 Consultancy companies
8.5 Government
8.6 Foreign universities/research institutions/labs
8.7 Other
Other (please specify)
9.1 Regarding internationalisation, does your firm offshore (or has your firm offshored) production or
any R&D activities? (Offshoring encompasses activities both internal and external to the firm for
the purposes of serving home country or global markets in a location outside the enterprise's home
6. Please indicate if your enterprise experienced innovation in the past 3 years (2006-2008) in any of the following. You may tick more than one option.
New to the
New to the
New to the
6.1 New products
6.2 New services
6.3 New or significantly improved methods of manufacturing or producing
6.4 New or significantly improved logistics, distribution or delivery methods for your inputs, goods and services
6.5 New or significantly improved supporting activities for your processes (e.g. purchasing, accounting,
maintenance systems etc.)
7. Regarding the development of the most important innovation of your firm in the last 3 years: who did you actively collaborate with and in which
geographical location? Region refers to a sub national area, please select all that apply.
Central &
Japan &
Rest of
7.1 Clients
7.2 Suppliers
7.3 Competitors
7.4 Consultancy companies
7.5 Government
Local Universities/Research
Foreign Universities/Research
7.8 Other
Other (please specify)
10. Please indicate how the following functions are performed by your enterprise, including different subsidiaries of the same firm. Please select all that
By your unit in
your location
At subsidiaries
of firm in a
At subsidiaries
of firm in a
Outsourced to a
partner in your
Outsourced to a
partner outside
your country in
a developed
Outsourced to a
partner outside
your country in
a developing
10.1 Strategic Management
10.2 Product development (research,
design and engineering)
10.3 Marketing, sales and account
10.4 Operations (manufacturing, service
10.5 Procurement, logistics, distribution
(obtaining, storing and transporting
inputs and outputs)
10.6 Corporate governance (legal, finance,
accounting, government relations)
10.7 Human resource management
10.8 Technology and process development
(maintenance, redesign of equipment)
10.9 Firm infrastructure (building and
maintenance IT systems)
10.10 Customers and after sales service
CIRCLE (Centre for Innovation, Research and Competence in the Learning
Economy) is a multidisciplinary research centre set off by several faculties at Lund
University and Blekinge Institute of Technology. CIRCLE has a mandate to conduct
multidisciplinary research and education on the following issues: Long-term
perspectives on innovation, structural change and economic growth,
Entrepreneurship and venture capital formation with a special focus on new ventures,
The dynamics of R&D systems and technological systems, including their impact on
entrepreneurship and growth, Regional innovation systems in different national and
international contexts and International comparative analyses of national innovation
systems. Special emphasis is done on innovation policies and research policies. 10
nationalities and 14 disciplines are represented among the CIRCLE staff.
The CIRCLE Electronic Working Paper Series are intended to be an instrument for
early dissemination of the research undertaken by CIRCLE researchers, associates
and visiting scholars and stimulate discussion and critical comment.
The working papers present research results that in whole or in part are suitable for
submission to a refereed journal or to the editor of a book or have already been
submitted and/or accepted for publication.
CIRCLE EWPs are available on-line at:
Available papers:
WP 2011/01
SMEs’ absorptive capacities and large firms’ knowledge spillovers: Micro
evidence from Mexico
Claudia de Fuentes and Gabriela Dutrénit
WP 2011/02
Comparing knowledge bases: on the organisation and geography of
knowledge flows in the regional innovation system of Scania, southern Sweden
Roman Martin and Jerker Moodysson
WP 2011/03
Organizational paths of commercializing patented inventions: The effects of
transaction costs, firm capabilities, and collaborative ties
Taehyun Jung and John P. Walsh
WP 2011/04
Global Innovation Networks: towards a taxonomy
Helena Barnard and Cristina Chaminade
WP 2011/05
Swedish Business R&D and its Export Dependence
Karin Bergman and Olof Ejermo
WP 2011/06
Innovation Policy Design: Identification of Systemic Problems
Charles Edquist
WP 2011/07
Regional Institutional Environment and Its Impact on Intra-firm and
Innovation Networks: A Comparative Case Study in China and
WP 2011/08
Entrepreneurship: Exploring the Knowledge Base
Hans Landström, Gouya Harirchi and Fredrik Åström
WP 2011/09
Policy coordination in systems of innovation: A structural-functional analysis
of regional industry support in Sweden
Magnus Nilsson and Jerker Moodysson
WP 2011/10
Urban Design in Neighbourhood Commodification
Ana Mafalda Madureira
WP 2011/11
Technological Dynamics and Social Capability: Comparing U.S. States and
European Nations
Jan Fagerberg, Maryan Feldman and Martin Srhoelec
WP 2011/12
Linking scientific and practical knowledge in innovation systems
Arne Isaksen and Magnus Nilsson
WP 2011/13
Institutional conditions and innovation systems: on the impact of regional
policy on firms in different sectors
Jerker Moodysson and Elena Zukauskaite
WP 2011/14
Considering adoption: Towards a consumption-oriented approach to
Josephine V. Rekers
WP 2010/01
Innovation policies for development: towards a systemic experimentation
based approach
Cristina Chaminade, Bengt-Ake Lundvall, Jan Vang-Lauridsen and KJ Joseph
WP 2010/02
From Basic Research to Innovation: Entrepreneurial Intermediaries for
Research Commercialization at Swedish ‘Strong Research Environments’
Fumi Kitagawa and Caroline Wigren
WP 2010/03 Different competences, different modes in the globalization of
A comparative study of the Pune and Beijing regions
Monica Plechero and Cristina Chaminade
WP 2010/04 Technological Capability Building in Informal Firms in the
Subsistence Sector In Tanzania: Assessing the Role of Gatsby Clubs
Astrid Szogs and Kelefa Mwantima
WP 2010/05
The Swedish Paradox – Unexploited Opportunities!
Charles Edquist
WP 2010/06
A three-stage model of the Academy-Industry linking process: the perspective
of both agents
Claudia De Fuentes and Gabriela Dutrénit
WP 2010/07
Innovation in symbolic industries: the geography and organisation of
knowledge sourcing
Roman Martin and Jerker Moodysson
WP 2010/08
Towards a spatial perspective on sustainability transitions
Lars Coenen, Paul Benneworth and Bernhard Truffer
WP 2010/09
The Swedish national innovation system and its relevance for the emergence
of global innovation networks
Cristina Chaminade, Jon Mikel Zabala and Adele Treccani
WP 2010/10
Who leads Research Productivity Change? Guidelines for R&D policy makers
Fernando Jiménez-Sáez, Jon Mikel Zabala and José L- Zofío
WP 2010/11
Research councils facing new science and technology
Frank van der Most and Barend van der Meulen
WP 2010/12
From new to the firm to new to the world. Effect of geographical proximity and
technological capabilities on the degree of novelty in emerging economies
Monica Plechero and Cristina Chaminade
WP 2010/13
Are knowledge-bases enough? A comparative study of the geography of
knowledge sources in China (Great Beijing) and India (Pune)
Cristina Chaminade
WP 2010/14
Regional Innovation Policy beyond ‘Best Practice’: Lessons from Sweden
Roman Martin, Jerker Moodysson and Elena Zukauskaite
WP 2010/15
Innovation in cultural industries: The role of university links
Elena Zukauskaite
WP 2010/16
Use and non-use of research evaluation. A literature review
Frank van der Most
WP 2010/17
Upscaling emerging niche technologies in sustainable energy: an international
comparison of policy approaches
Lars Coenen, Roald Suurs and Emma van Sandick
WP 2009/01
Building systems of innovation in less developed countries: The role of
intermediate organizations.
Szogs, Astrid; Cummings, Andrew and Chaminade, Cristina
WP 2009/02
The Widening and Deepening of Innovation Policy: What Conditions Provide
for Effective Governance?
Borrás, Susana
WP 2009/03
Managerial learning and development in small firms: implications based on
observations of managerial work
Gabrielsson, Jonas and Tell, Joakim
WP 2009/04
University professors and research commercialization: An empirical test of the
“knowledge corridor” thesis
Gabrielsson, Jonas, Politis, Diamanto and Tell, Joakim
WP 2009/05
On the concept of global innovation networks
Chaminade, Cristina
WP 2009/06
Technological Waves and Economic Growth - Sweden in an International
Perspective 1850-2005
Schön, Lennart
WP 2009/07
Public Procurement of Innovation Diffusion: Exploring the Role of Institutions
and Institutional Coordination
Rolfstam, Max; Phillips, Wendy and Bakker, Elmer
WP 2009/08
Local niche experimentation in energy transitions: a theoretical and empirical
exploration of proximity advantages and disadvantages
Lars Coenen, Rob Raven, Geert Verbong
WP 2009/9
Product Development Decisions: An empirical approach to Krishnan and Ulrich
Jon Mikel Zabala, Tina Hannemann
WP 2009/10
Dynamics of a Technological Innovator Network and its impact on
technological performance
Ju Liu, Cristina Chaminade
WP 2009/11
The Role of Local Universities in Improving Traditional SMEs Innovative
Performances: The Veneto Region Case
Monica Plechero
WP 2009/12
Comparing systems approaches to innovation and technological change for
sustainable and competitive economies: an explorative study into conceptual
commonalities, differences and complementarities
Coenen, Lars and Díaz López, Fernando J.
WP 2009/13
Public Procurement for Innovation (PPI) – a Pilot Study
Charles Edquist
WP 2009/14
Outputs of innovation systems: a European perspective
Charles Edquist and Jon Mikel Zabala
WP 2008/01
R&D and financial systems: the determinants of R&D expenditures in the
Swedish pharmaceutical industry
Malmberg, Claes
WP 2008/02
The Development of a New Swedish Innovation Policy. A Historical Institutional
Persson, Bo
WP 2008/03
The Effects of R&D on Regional Invention and Innovation
Olof Ejermo and Urban Gråsjö
WP 2008/04
Clusters in Time and Space: Understanding the Growth and Transformation of
Life Science in Scania
Moodysson, Jerker; Nilsson, Magnus; Svensson Henning, Martin
WP 2008/05
Building absorptive capacity in less developed countries
The case of Tanzania
Szogs, Astrid; Chaminade, Cristina and Azatyan, Ruzana
WP 2008/06
Design of Innovation Policy through Diagnostic Analysis:
Identification of Systemic Problems (or Failures)
Edquist, Charles
WP 2008/07
The Swedish Paradox arises in Fast-Growing Sectors
Ejermo, Olof; Kander, Astrid and Svensson Henning, Martin
WP 2008/08
Policy Reforms, New University-Industry Links and Implications for Regional
Development in Japan
Kitagawa, Fumi
WP 2008/09
The Challenges of Globalisation: Strategic Choices for Innovation Policy
Borrás, Susana; Chaminade, Cristina and Edquist, Charles
WP 2008/10
Comparing national systems of innovation in Asia and Europe: theory and
comparative framework
Edquist, Charles and Hommen, Leif
WP 2008/11
Putting Constructed Regional Advantage into Swedish Practice? The case of
the VINNVÄXT initiative 'Food Innovation at Interfaces'
Coenen, Lars; Moodysson, Jerker
WP 2008/12
Energy transitions in Europe: 1600-2000
Kander, Astrid; Malanima, Paolo and Warde, Paul
WP 2008/13
RIS and Developing Countries: Linking firm technological capabilities to
regional systems of innovation
Padilla, Ramon; Vang, Jan and Chaminade, Cristina
WP 2008/14
The paradox of high R&D input and low innovation output: Sweden
Bitarre, Pierre; Edquist, Charles; Hommen, Leif and Ricke, Annika
WP 2008/15
Two Sides of the Same Coin? Local and Global Knowledge Flows in Medicon
Moodysson, Jerker; Coenen, Lars and Asheim, Bjørn
WP 2008/16
Electrification and energy productivity
Enflo, Kerstin; Kander, Astrid and Schön, Lennart
WP 2008/17
Concluding Chapter: Globalisation and Innovation Policy
Hommen, Leif and Edquist, Charles
WP 2008/18
Regional innovation systems and the global location of innovation activities:
Lessons from China
Yun-Chung, Chen; Vang, Jan and Chaminade, Cristina
WP 2008/19
The Role of mediator organisations in the making of innovation systems in
least developed countries. Evidence from Tanzania
Szogs, Astrid
WP 2008/20
Globalisation of Knowledge Production and Regional Innovation Policy:
Supporting Specialized Hubs in the Bangalore Software Industry
Chaminade, Cristina and Vang, Jan
WP 2008/21
Upgrading in Asian clusters: Rethinking the importance of interactive-learning
Chaminade, Cristina and Vang, Jan
WP 2007/01
Path-following or Leapfrogging in Catching-up: the Case of Chinese
Telecommunication Equipment Industry
Liu, Xielin
WP 2007/02
The effects of institutional change on innovation and productivity growth in the
Swedish pharmaceutical industry
Malmberg, Claes
WP 2007/03
Global-local linkages, Spillovers and Cultural Clusters: Theoretical and
Empirical insights from an exploratory study of Toronto’s Film Cluster
Vang, Jan; Chaminade, Cristina
WP 2007/04
Learning from the Bangalore Experience: The Role of Universities in an
Emerging Regional Innovation System
Vang, Jan; Chaminade, Cristina.; Coenen, Lars.
WP 2007/05
Industrial dynamics and innovative pressure on energy -Sweden with
European and Global outlooks
Schön, Lennart; Kander, Astrid.
WP 2007/06
In defence of electricity as a general purpose technology
Kander, Astrid; Enflo, Kerstin; Schön, Lennart
WP 2007/07
Swedish business research productivity – improvements against international
Ejermo, Olof; Kander, Astrid
WP 2007/08
Regional innovation measured by patent data – does quality matter?
Ejermo, Olof
WP 2007/09
Innovation System Policies in Less Successful Developing countries: The case
of Thailand
Intarakumnerd, Patarapong; Chaminade, Cristina
WP 2006/01
The Swedish Paradox
Ejermo, Olof; Kander, Astrid
WP 2006/02
Building RIS in Developing Countries: Policy Lessons from Bangalore, India
Vang, Jan; Chaminade, Cristina
WP 2006/03
Innovation Policy for Asian SMEs: Exploring cluster differences
Chaminade, Cristina; Vang, Jan.
WP 2006/04
Rationales for public intervention from a system of innovation approach: the
case of VINNOVA.
Chaminade, Cristina; Edquist, Charles
WP 2006/05
Technology and Trade: an analysis of technology specialization and export
Andersson, Martin; Ejermo, Olof
WP 2006/06
A Knowledge-based Categorization of Research-based Spin-off Creation
Gabrielsson, Jonas; Landström, Hans; Brunsnes, E. Thomas
WP 2006/07
Board control and corporate innovation: an empirical study of small
technology-based firms
Gabrielsson, Jonas; Politis, Diamanto
WP 2006/08
On and Off the Beaten Path:
Transferring Knowledge through Formal and Informal Networks
Rick Aalbers; Otto Koppius; Wilfred Dolfsma
WP 2006/09
Trends in R&D, innovation and productivity in Sweden 1985-2002
Ejermo, Olof; Kander, Astrid
WP 2006/10
Development Blocks and the Second Industrial Revolution, Sweden 1900-1974
Enflo, Kerstin; Kander, Astrid; Schön, Lennart
WP 2006/11
The uneven and selective nature of cluster knowledge networks: evidence from
the wine industry
Giuliani, Elisa
Informalinvestors andvalueadded:Thecontributionofinvestors’ experientially
Politis, Diamanto; Gabrielsson, Jonas
Politis, Diamanto; Gabrielsson, Jonas
WP 2006/14
Inventive and innovative activity over time and geographical space: the case of
Ejermo, Olof
WP 2005/1
Constructing Regional Advantage at the Northern Edge
Coenen, Lars; Asheim, Bjørn
WP 2005/02
From Theory to Practice: The Use of the Systems of Innovation Approach for
Innovation Policy
Chaminade, Cristina; Edquist, Charles
WP 2005/03
The Role of Regional Innovation Systems in a Globalising Economy:
Comparing Knowledge Bases and Institutional Frameworks in Nordic Clusters
Asheim, Bjørn; Coenen, Lars
WP 2005/04
How does Accessibility to Knowledge Sources Affect the Innovativeness of
Corporations? Evidence from Sweden
Andersson, Martin; Ejermo, Olof
WP 2005/05
Contextualizing Regional Innovation Systems in a Globalizing Learning
Economy: On Knowledge Bases and Institutional Frameworks
Asheim, Bjørn; Coenen, Lars
WP 2005/06
Innovation Policies for Asian SMEs: An Innovation Systems Perspective
Chaminade, Cristina; Vang, Jan
WP 2005/07
Re-norming the Science-Society Relation
Jacob, Merle
WP 2005/08
Corporate innovation and competitive environment
Huse, Morten; Neubaum, Donald O.; Gabrielsson, Jonas
WP 2005/09
Knowledge and accountability: Outside directors' contribution in the corporate
value chain
Huse, Morten, Gabrielsson, Jonas; Minichilli, Alessandro
WP 2005/10
Rethinking the Spatial Organization of Creative Industries
Vang, Jan
WP 2005/11
Interregional Inventor Networks as Studied by Patent Co-inventorships
Ejermo, Olof; Karlsson, Charlie
WP 2005/12
Knowledge Bases and Spatial Patterns of Collaboration: Comparing the
Pharma and Agro-Food Bioregions Scania and Saskatoon
Coenen, Lars; Moodysson, Jerker; Ryan, Camille; Asheim, Bjørn; Phillips, Peter
WP 2005/13
Regional Innovation System Policy: a Knowledge-based Approach
Asheim, Bjørn; Coenen, Lars; Moodysson, Jerker; Vang, Jan
WP 2005/14
Face-to-Face, Buzz and Knowledge Bases: Socio-spatial implications for
learning and innovation policy
Asheim, Bjørn; Coenen, Lars, Vang, Jan
WP 2005/15
The Creative Class and Regional Growth: Towards a Knowledge Based
Kalsø Hansen, Høgni; Vang, Jan; Bjørn T. Asheim
WP 2005/16
Emergence and Growth of Mjärdevi Science Park in Linköping, Sweden
Hommen, Leif; Doloreux, David; Larsson, Emma
WP 2005/17
Trademark Statistics as Innovation Indicators? – A Micro Study
Malmberg, Claes
... But the kind of partners they search for give room to some discussion. While some authors suggest that they usually prefer networks with smaller companies in order not to expose critical knowledge to potential competitors (Sinha & Cusumano, 1991;Barnard & Chaminade, 2011;Grutzman, Halme & Reiner, 2009), others propose that large firms are not prone to establish cooperative projects with smaller firms since this action will not provide the former with greater market power, thus networks would tend to be constituted by firms of similar sizes (Roller, Tombak & Siebert, 1997). ...
... In geographical terms, cohesion seems to play an important role: R&D networks that are too dispersed experience worse technological performance (Barnard & Chaminade, 2011;Dyer & Powell, 2002). In this regard we should approach geography as a proxy for other influent variables in the process, such as cultural background, local market characteristics, language barriers and difficulties involving coordination from long distance. ...
... Follows a summary of the main features presented in this section, gathering evidence on R&D networks' outcomes regarding the three analyzed dimensions: a) Firms engaging in technological cooperation outperform those that do not in terms of innovative performance b) R&D collaboration -especially at the international level -is positively associated w ith higher innovation expenditures c) Firms' reliance on external know ledge tends to increase its absorptive capacity d) R&D netw orks provide firms w ith better corporate results through better innovative outcomes e) R&D netw orks are highly dependent on external subsidies to achieve higher rates of R&D intensity Faems et al, 2010;Zeng, Xie & Tam, 2010;Cusmano, 2001;Beaudry, 2011;De Jong & Freel, 2010;Siebert, 1996;Czarnitzki, Ebersberger & Fier, 2007;Franco, Marzucchi & Montresor, 2011;Bogliacino & Pianta, 2010;Surroca Aguilar & Santamaría Sánchez, 2006;Stenbacka & Tombak, 1998 Corporate Performance a) R&D cooperation improves corporate performance and industry competitiveness b) International R&D collaboration provides firms w ith strategic flexibility c) Financial markets perceive international and cross-sectoral alliances as positive d) Commercialization of a given project involving R&D collaboration drives the project's positive or negative evaluation by participants e) Benefits from R&D cooperation seem to be largely intangible f) Timing of evaluation is key , 1994;1997a;Hagedoorn, 2002;Bayona, Corredor & Santamaría, 2006 Netw ork Structure & Management a) Importance of quality of coordination and levels of know ledge sharing for success in R&D netw orks b) Risks involved in R&D cooperation are mainly related to technological spillovers to (potential) competitors c) Vertical netw orks are easier to manage than horizontal ones d) Research consortia outcomes have positive association w ith levels of R&D spillovers and negative association w ith the degree of market competition betw een members of consortia e) R&D netw orks that are too geographically dispersed incur in w orse technological performance f) International linkages matter only in combination w ith domestic ones G) collaborative RTD policy should focus on a large number of small projects instead of on a few large-scale ones Dyer & Powell, 2002;Tao & Wu, 1997;Branstetter & Sakakibara, 2002;Barnard & Chaminade, 2011;Srholec, 2011;Broekel, Schimke and Brenner, 2011 ...
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Innovation is increasingly becoming an internationalized process. A strategy that has recently been playing a central role in this regard is that of R&D collaboration. In the case of firms this is mainly driven by the search of more efficient operations, reduced costs and risks of innovative activities, as well as access to pools of knowledge available outside the traditional organizational boundaries. However, relationships among firms increase complexity of managerial processes, thus evidencing the need for closer coordination between agents, which is expected to be even more complex when these connections happen between companies from different nations, provided that there are additional transaction costs involved, e.g., language, institutional settings, etc. In the European context, efforts have been made towards organizing an integrated Innovation System across the continent, favoring international linkages within the European Union. This situation poses a need for specialized research to focus on the improvement of such initiatives to strengthen the bloc’s competitiveness. Moreover, we stress the case of the Spanish Innovation System, one of the largest economies of the European Union with an Innovation System that occupies a relatively laggard position in the EU. The approach undertaken in this dissertation focuses on determining the influential aspects of firms’ results, which are expected to lie on three fundamental dimensions: Microeconomic, Contextual (project-specific), and Macroeconomic. Furthermore, behavioral patterns regarding firms’ outcomes are assessed, aiming at providing policymakers with workable information for programs’ evaluation and improvement. To cope with these goals we develop logistic regressions to identify determinants of success in terms of: a) technological outcomes; b) market achievements; and c) future expected accomplishments. Data is gathered from Eureka’s Final Reports (2000-2005 and 2006- 2008) from Spain (research focus), Italy, France, United Kingdom, and Germany (benchmark countries). Results highlight the core importance of the Contextual Dimension, whereas the National Innovation System to which a given firm belongs has marginal relevance (Macroeconomic Dimension), and firms’ characteristics (Microeconomic Dimension) do not seem to be related to projects’ achievements. This puts special emphasis on the fundamental role played by network coordination. The lack of significance of the Microeconomic Dimension as a determinant of achievements poses some implications for the use of quasi-experimental methodologies in assessing the effectiveness of innovation policies. Behavioral patterns were identified through loglikelihood clusters. Results confirm trends suggested by Fischer and Molero (2012), where firms fall under three categories: Inventors, Consistent Innovators, and Risky Innovators. Implications for the specific case of Spain are offered, where international R&D cooperation seems to be a fundamental strategy for sustainable development of firms located in this particular country.
... Hitherto, almost all evidence is based on the analysis of whole countries (Castellacci and Archibugi, 2008;Filippetti and Peyrache, 2011;Stöllinger, 2013;Kemeny, 2010;Fagerberg et al., 2007) or on one particular industry or region (Schmitz, 2007;Cusmano et al., 2010), while there are very few systematic comparative analysis of firms from different industries across the globe (Barnard and Chaminade, 2011). ...
... Answering the survey was not mandatory and there might be a bias in the response rate towards firms that either are more active innovators or firms that establish more global networks, thus the sample may not be completely representative of the firms population in terms of size, ownership, innovation performance, and organisation forms which might influence the results of the analysis. Barnard and Chaminade (2011) Despite the limitations of the sample, we deem it adequate for the type of research questions investigated in this paper. We did not attempt to investigate the extent of the phenomenon but if there were new to the world innovators in emerging economies and, if so, what were the micro and meso characteristics that could explain this innovative behaviour. ...
... We identified those indicators based on previous studies that focus on the analysis of collaboration to foster innovation. Structural factors related to firm size and type of firm, behavioural factors related to innovation decisions (De Fuentes and Dutrenit, 2012;Laursen et al., 2011), and the extent of global networks for exploitation, collaboration, and generation (Barnard and Chaminade, 2011;Chaminade and Plechero, 2015). Regarding the characteristics of global networks they indicate that a firm with more global networks will be able to have higher rates of exploitation, but also will be able to access more diverse sources of knowledge. ...
Recent literature shows that differences in structural characteristics at country level are important determinants of the innovative capacities and growth performance of different countries. Based on firm-level data collected from a survey, this study identifies who are the world leaders, followers, and marginalised firms in a sample of nine countries and a selection of industries in terms of firms' characteristics, the characteristics of the region where they are located, as well as the firm strategies to engage in global innovation networks. Our results, based on a small sample, show that some firms from emerging economies are among the exclusive group of world leaders and some firms from developed economies are among world followers and marginalised. Without attempting to generalise our results, the findings confirm the changing role of some firms in emerging economies from followers to world leaders in innovation.
... В дослідженні фокусується увага на сучасних тенденціях розвитку глобальних інноваційних мереж, а також визначається їх роль та значення у розвитку сучасної світової економіки. [14,[5][6][7][8][9][10][11][12][13][14][15][16][17][18][19][20][21][22][23][24], шведським вченим Б. Лундваллом [17] та американським професором Р. Нельсоном [18]. Проте, дослідження названих авторів відрізняються за своїми напрямами та завданнями: К. Фрімен виділяє інституційний контекст інноваційної діяльності, Б. Лундвалл вивчає особливості НІС, а Р. Нельсон робить акцент на питаннях наукової та технологічної політики. ...
... [8] Під глобальними інноваційними мережами розуміть глобально організовану мережу взаємопов'язаних та інтегрованих функцій і операцій комерційних та некомерційних організацій, що займаються розробкою або поширенням інновацій. [10] Глобальні інноваційні мережі можна розподілити на такі групи [8]: ...
Under the megatrend, we mean large-scale technological, economic, social, political changes that occur slowly, but in the long run, when they are rooted, they substantially and permanently affect most of the processes in society. Such relative stability in the trajectory of the main forces of change can predict some elements of medium and long-term future changes. The article investigates such megatrends of the development of global innovation networks as the structural nature of the global innovation system, the development of systemic interconnections in the field of innovation, the interaction of national innovation systems and global, the internationalization of innovation activity, and the paradigm of "open innovation". The methodological principles and structural elements of the concept of the national innovation system are determined in the paper, the connection of national innovation systems with the phenomenon of internationalization of the innovation sphere is explored. The theoretical principles of the phenomenon of internationalization of innovation activity are investigated, as well as the preconditions for the emergence of the concept of "open innovation" and its current trends have been established. The concept of open innovation is an important precondition for the emergence and functioning of global innovation networks. The paper analyzes the genesis and specificity of the phenomenon of global innovation networks, outlines their structure and dynamics. It has been determined that global innovation networks play an important role in the development of the modern world economy, as they stimulate international cooperation in the innovation sphere, transfer of knowledge to the world economy and general scientific and technological development and growth of world production.
... В дослідженні фокусується увага на сучасних тенденціях розвитку глобальних інноваційних мереж, а також визначається їх роль та значення у розвитку сучасної світової економіки. [14,[5][6][7][8][9][10][11][12][13][14][15][16][17][18][19][20][21][22][23][24], шведським вченим Б. Лундваллом [17] та американським професором Р. Нельсоном [18]. Проте, дослідження названих авторів відрізняються за своїми напрямами та завданнями: К. Фрімен виділяє інституційний контекст інноваційної діяльності, Б. Лундвалл вивчає особливості НІС, а Р. Нельсон робить акцент на питаннях наукової та технологічної політики. ...
... [8] Під глобальними інноваційними мережами розуміть глобально організовану мережу взаємопов'язаних та інтегрованих функцій і операцій комерційних та некомерційних організацій, що займаються розробкою або поширенням інновацій. [10] Глобальні інноваційні мережі можна розподілити на такі групи [8]: ...
In this article is analyzed the level of intra-industry trade with Ukraine, the latest publications and the substantiated purpose and methodology of work are investigated. The issue of intra-industry trade of Ukraine and the EU as a factor of the effectiveness of integration was examined. Calculations of the total quantity and value of a number of imported and exported goods of Ukraine for January-September of 2017 were made; calculated the index of mutual trade of certain goods, which characterizes the level of intra-industry trade between the investigated objects. As a result, a comparative analysis of the Grubel-Lloyd index of goods of certain groups was carried out, and prospective and decadent groups were identified. It is stressed that the Ukrainian producer actively cooperates with the EU in certain industries, but trade in some of the studied product groups is in active development. In the end, an understanding of the prospects and current problems of Ukraine's integration into trade with the countries of the European Union was presented. There is a conclusion that, as of 2017, the dynamics of growth of the index of intra-industry trade between Ukraine and the EU is positive for 60% of goods and for others 40% is negative or more stable.
... They do this by, for example, locating R&D centres and sourcing technology and knowledge abroad. If we look at the location of R&D centres around the world, a global innovation network emerges (GIN) (Zander 2002;Ernst 2000;Shin, Kraemer, and Dedrick 2009;Barnard and Chaminade 2011). However, as studies of R&D internationalisation have up until now focused on the bilateral relationships between countries, the structure and workings of GINs are not fully understood (Tassey 2007). ...
... If we consider all R&D centre locations around the world, a GIN emerges (Zander 2002;Ernst 2000;Shin, Kraemer, and Dedrick 2009;Barnard and Chaminade 2011). Although the very nature of a GIN calls for a many-to-many approach, studies of R&D and innovation internationalisation have up until now looked at pairs of countries (Gassler and Nones 2008;Kumar 2008;Pittiglio, Sica, and Villa 2009). ...
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We look at the structure and evolution of an information and communication technology (ICT) global innovation network (GIN) by mapping the locations of R&D centres belonging to a group of multinational ICT enterprises. We found that the number of countries and connections have increased in a very short time, and that most of the newcomers have come from Africa, Asia and South America. We show that a country’s network position affects the creation and intensity of R&D linkages with other countries in the network. This suggests that the evolution of the ICT GIN is driven by, among other things, the preferential attachment mechanism, i.e. countries tend to connect to those countries which have more links. A country’s position in the network also moderates the effect of standard determinants of innovation i, such as geographic distance. Hence, network position explains the creation of R&D linkages between such distant countries as the US, China or India.
... Global production networks and the internationalization of production activities have been widely studied by scholars in economic geography (Coe et al., 2008;Dicken et al., 2001;Henderson et al., 2002) and in international business (Cantwell & Piscitello, 2002, 2005Dunning, 2001;Dunning & Lundan, 2009). But it is only recently that scholars in these fields of research have started to pay attention to the globalization of innovation activities and to the surge of GINs (Alvstam & Shamp, 2005;Archibugi & Iammarino, 2002;Barnard & Chaminade, 2011;Freeman et al., 2010;Plechero & Chaminade, 2013;Zanfei, 2000). ...
... The findings underline the fact that firms in regions with RISs that are neither too thick nor too thin engage more in GINs. What the results seem to suggest-in line with Barnard and Chaminade (2011)-is that engaging in GINs is costly and hard to maintain, and that firms engage in different forms of GIN only when they cannot find the resources they need to innovate in their close proximity. Firms that are located in thick regions, those with a Tier 1 RIS, tend to network for innovation with other firms and organizations that are in close proximity, or with domestic actors, so they may not have a strong need to develop asset-seeking strategies at the global level. ...
Access to global innovation networks (GINs) has been unequal across the regions of the world. While certain regions are considered knowledge hubs in GINs, others still remain marginalized; this points to the role of regional innovation systems (RISs) in the emergence and development of GINs. Using firm-level data collected through a survey and case studies in 2009–2010, this paper systematically compares the patterns of global networks in the information and communications technology industry in a selection of European, Chinese and Indian regions. The results show that GINs are more common in regions which are not organizationally and institutionally thick, suggesting that GINs may be a compensatory mechanism for weaknesses in the RIS.
... Mostly dealing with international trade and finance, the researches analyzes the failure of compensation and failure of representation in global redistribution [4], influence of globalizing trade on job markets in different parts of the World [5], the link between the size of the State and financial and trade globalization (more open the economy is, the bigger public sector is needed to compensate globalization) [6], the global innovation networks as a source to compensate firms from "weaker" contexts [7]. ...
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The evolution of such economic categories as: global rent, global expropriation, compensatory globalization in their interrelation in the conditions of hyperglobalization, neo-liberalism and neo-medievalism are considered. The following possibilities for the removal of global monopoly rent are suggested: control over the markets of productive resources, markets of finished products, global infrastructure, the rule-setting, etc. Two forms of global expropriation (violation and cooperation) regarding its sources and results are considered. The phenomenon of compensatory globalization from the standpoint of global winners and global losers is described. Further development of economic analysis of relations regarding global monopoly rent in the framework of global political economy is suggested. ГЛОБАЛЬНА ЕКСПРОПРІАЦІЯ, ГЛОБАЛЬНА РЕНТА ТА КОМПЕНСАТОРНА ГЛОБАЛІЗАЦІЯ Кобилянська А.В. Розглянуто еволюцію таких економічних категорій як: глобальна рента, глобальна експропріація, компенса-торна глобалізація в їх взаємозв'язку в умовах гіперглобалізації, неолібералізму і неомедієвалізму. Запропоновано такі можливості для вилучення глобальної монопольної ренти як: контроль над ринками виробничих ресурсів, ринками готової продукції, глобальною інфраструктурою, встановленням правил тощо. Описане явище компен-саторної глобалізації для глобальних переможців і глобальних переможених: переможці прагнуть компенсувати ризики інвестування, в більш широкому сенсі, в переможених від глобалізації та їхні ринки, переможені-компен-сувати втрати від монополізації. У статті окреслено можливості подальшого розвитку економічного аналізу відносин стосовно глобальної монопольної ренти та дефіциту глобального економічного управління в рамках глобальної політичної економії. Ключові слова: глобальна експропріація, глобальна рента, компенсаторна глобалізація, глобальна економіка, глобальні переможці та глобальні переможені, глобальний перерозподіл. ГЛОБАЛЬНАЯ ЭКСПРОПРИАЦИЯ, ГЛОБАЛЬНАЯ РЕНТА И КОМПЕНСАТОРНАЯ ГЛОБАЛИЗАЦИЯ Кобылянская А.В. В статье рассматривается развитие таких экономических категорий, как: глобальная рента, глобальная экспроприация, компенсаторная глобализация в их взаимосвязи в условиях гиперглобализации, неолиберализма и неосредневековья. Были предложены такие возможные опции извлечения глобальной монопольной ренты, как: контроль над рынками производственных ресурсов, рынками готовой продукции, глобальной инфраструктурой, нормотворчеством и т.д. Были рассмотрены две формы глобальной экспроприации (насилие и сотрудничество) с точки зрения ее источников и результатов, описан феномен компенсаторной глобализации с позиции глобаль-14-Інтелект ХХІ № 1'2019-14-СВІТОВА ЕКОНОМІКА ТА МІЖНАРОДНІ ВІДНОСИНИ ных победителей и глобальных проигравших. В статье предлагается дальнейшее развитие экономического ана-лиза глобальных монопольных отношений в рамках глобальной политической экономии. Ключевые слова: глобальная экспроприация, глобальная рента, компенсаторная глобализация, глобальная экономика, глобальные победители vs глобальных проигравших, глобальное перераспределение.
... This study adapts one such basic definition in order to examine the PS.Therefore, it frequently refers to dynamic innovation networks (DINs). The concept is defined innovation network (DIN) emerges from the interconnected and integrating practices of actors that engage in innovation activities (adapted fromBarnard & Chaminade, 2011b). ...
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Collaborative innovation processes in unpredictable environments are a challenge for traditional management. But new demands in a global digital society push public and corporate leadership to collaborate ad hoc, without predictable goals and planned working rules. In this study, an actor-network approach (ANT) is combined with critical incident technique (CIT) to elaborate dynamic network principles for a new real-time foresight (RTF). Real-time foresight replaces traditional planning and strategic management in ad hoc multi-sector collaborations. Although ANT originates from science and technologies studies, it is here applied to a management problem due to ist ability to merge voluntaristic and evolutionary managerial components and micro- and macro perspectives. The investigation is placed in an exemplary management field of high dynamics: global disaster management. From process analysis and from comparison of three dynamic innovation networks that emerged around Indian coastal villages after Tsunami 2004, five dynamic network patterns are obtained which underly successful collaborative innovation processes. These dynamic structures build the agenda for a new real-time foresight, and for an instrument to evaluate in real-time the emergence of dynamic innovation networks (DINs).
... Different types of GIN can be identified according to: 1) the mechanism of coordination of the network members: formal / informal (Borrás and Lorentzen, 2011); 2) the degree of interactions with the external environment: open / closed (Knell, 2010); 3) the nature of interactions with simultaneous consideration of the three primary characteristics (globality, innovativeness and networkness): balanced, focused on innovation and on the use of global assets, on network interactions, on participation in global networks (Barnard and Chaminade, 2011); and 4) the nature and degree of participation of developing countries: internal network in which global companies derive offshore to Asian affiliates or outsource specialized Asian suppliers the individual stages of innovation process; own networks of the Asian firms; international public-private R&D consortia; informal social network of students / employees in the research field (Ernst, 2009). ...
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The article discusses an important issue of Russian integration into the global network cooperation in innovation. The first part of the study addresses differences in types of knowledge flows between the country of the firm-innovator and the host country. Three main directions of globalization of innovation are identified. Each of the given cases provides insights on the possible forms of cooperation and the degree of codification of new knowledge arising within the framework of the innovation process. The second part of the article is devoted to global innovation network (GIN) concept, which combines all three types of globalization of innovation. The characterizing features of GIN are highlighted. The key reasons for its formation are examined. The third section reflects research results on the degree and directions of integration of Russian companies in the world economic processes. The most promising areas of innovation networking are given. The factors contributing to the development of Russian-European cooperation network as a first step to enter the world arena and integration into global innovation networks are defined.
Through a comparative analysis of technology management at the component level by wind turbine manufacturers from Europe and China, this article compares strategies of internalisation of core technology components by European and Chinese lead firms and outlines how different internalisation strategies impact the networks established by the two types of lead firms. Building on the concept of governance developed by the global value chain literature, the article identifies two different types of networks: European lead firms internalise core technology components and keep strong captive or relational ties with key component suppliers, whereas Chinese lead firms modularise and externalise core technology components, hence adopting a more flexible approach to technology management. The latter model mirrors a strategy of overcoming technological barriers by tapping into knowledge through global innovation networks. The article contributes to the network governance literature by introducing scales of component technology complexity and lead firm capabilities for understanding network constructs.
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The process of knowledge production exhibits a very distinctive geography. This article argues that this geography is fundamental, not incidental, to the innovation process itself: that one simply cannot understand innovation properly if one does not appreciate the central role of spatial proximity and concentration in this process. The goal of this article is to demonstrate why this is true, and to examine how innovation systems at the subnational scale play a key part in producing and reproducing this uneven geography over time. This article addresses four key issues. First, it looks at the reason why location matters when it comes to innovative activity. Second, it turns to examine regional innovation systems, and the role played by them in generating and circulating new knowledge leading to innovation. Third, the article considers the relationship between regional systems of innovation and institutional frameworks at the national level. Finally, the relationship between local and global knowledge flows is examined.
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The vast literature of systems of innovation is rich in theoretical and empirical studies about the complexity and institutionally-embedded processes of interaction and learning. So far, however, this literature has not studied in a comprehensive manner the nature and types of strategic choices that public actors in systems of innovation are facing given the ever-changing social, economic and technological contexts. This chapter undertakes a first step designing an analytical model to address this fundamental issue. The specific point of departure is the set of challenges that the process of globalisation has been posing to systems of innovation in industrialised and developing countries, past and present. The next section approaches the general problem about strategic choices for systems of innovation and reviews succinctly the policy-related literature in the field, pointing at the missing elements and uncovered issues. After that, the chapter delves into the issue of uncertainty and selectivity, two core preliminary aspects for defining strategic choices. Last, the fifth section deals with systemic problems in the view of the globalisation context, and addresses the critical issue of designing a method to help public actors spelling out objectives and instruments unfolding their specific strategic choices for systems of innovation.
Inter-firm relations are not new. But fast developments in technology and globalization have led to increased opportunities for international alliances, and an upsurge in the interest in inter-organizational relations. With the time ripe for a unified theory of collaboration, Inter-firm Collaboration, Learning and Networks surveys the current field, connects differing perspectives and answers questions about who should collaborate, why, and how. Emphasizing learning and innovation, this book offers an integrated account of the key issues in the design and management of inter-firm relations and networks. It takes a uniquely interdisciplinary approach, bringing together perspectives from economics, sociology and management to offer a new kind of book on this subject. Supporting theory, the book includes illustrative case examples taken from a variety of firm, network and industry types. Coherent and wide-reaching, Inter-firm Collaboration, Learning and Networks provides students and academics in economics, business, sociology, social psychology and economic geography with the tools required to understand this topical and highly relevant subject.
Using material from surveys of multinational enterprise (MNE) production subsidiaries and laboratories operating in the UK, the paper seeks to discern vital changes in the roles of such R&D facilities. From the primarily tactical and technologically dependent role of adapting established group products for the local market these labs now take more committed positions in support of their group's strategic competitiveness. This can involve a much more profound involvement in original product development, or inputs into programmes of pre-competitive (basic or applied) research to support the longer term evolution of the core technology of the MNE group. It is suggested that this evolution of decentralised labs' positioning in MNE knowledge strategies implies (i) an increasing involvement in product development rather than adaptation, (ii) an interdependent rather than dependent position in group technology programmes, (iii) increased relevance of supply side influences (host country technology competencies, capacities and heritage), (iv) decline of centralising forces on R&D (e.g., economies of scale, communication and co-ordination problems, concerns of knowledge security).
As developing and transition economies opened up to the global economy in recent years, a number of local firms not only survived the battle for markets at home, they expanded internationally through exports and foreign direct investment (FDI) to become fledgling multinational enterprises (MNEs) in their own right. By 2007, the more prominent emerging-market MNEs (hereafter referred to as EMNEs) included firms such as China's Huawei in telecommunications equipment, Mexico's Cemex in cement, Russia's Gazprom in energy, India's Tata Consultancy Services in information technology (IT) services, and Brazil's Embraer in regional jets. Many more firms in emerging economies were preparing to go down the same path in the future. Business magazines, such as BusinessWeek (2006) and the Economist (2007), trumpeted this trend with cover stories on “emerging giants” or “globalization's offspring” and illustrated the disruptive effects EMNEs were having on established Western multinationals. Consulting companies, such as McKinsey & Co. and the Boston Consulting Group (BCG), also took notice of these potential clients. There was a parallel increase in studies on EMNEs by international business (IB) scholars, although no consensus emerged on whether and how EMNEs differed from multinationals that had come before.
To match the global demand and supply of innovation, businesses increasingly internationalise their innovation activities while opening their innovation process by collaborating with external partners (e.g., suppliers, customers, universities). This book examines what drives these global innovation networks across different industries, how they are related to companies' overall strategies, whether they are accessible for small and medium-sized enterprises (SMEs) and what the consequences are.
The assumption that 'local search' constrains the direction of corporate R&D is central in evolutionary perspectives on technological change and competition. In this paper, we propose a network-analytic approach for identifying the evolution of firms' technological positions. The approach (I) permits graphical and quantitative assessments of the extent to which firms' search behavior is locally bounded, and (2) enables firms to be positioned and grouped according to the similarities in their innovative capabilities. The utility of the proposed framework is demonstrated by an analysis of strategic partnering and the evolution of the technological positions of the 10 largest Japanese semiconductor producers from 1982 to 1992.