1. University, Industry, Government
Measuring Triple Helix in Netherlands, Russia, Turkey, Iran; Webometrics
approach
Abdalsamad Keramatfar,a Fereshteh Esparaeinb
a Scientific Information Center (SID); email: keramatfar.a.s@gmail.com
b Shahed University; email: esparaein@gmail.com
Abstract
In present societies, knowledge is known as the main source of Economic prosperity and
Societies that derive their economical power from the production and diffusion of information
and knowledge are referred to as knowledge-based societies or economies. This paper aimed to
measure Triple Helix for studying the innovation infrastructure in Iran in compare with
Netherlands, Russia, and Turkey. This research is based on Webometrics methods and we
performed this research in two ways: first, we used the number of hits and co-occurrence of
“university”, “industry” and “government”. Second, we confined our search to Rich Files. In first
way; the results show that in selected countries, “University”, “Industry” And “Government” are
more integrated in Netherlands following by Russia, Turkey and Iran in recent years. Iran in
compare with other countries has no a good situation. In second way; the results show a different
situation. Netherlands has higher value in this indicator, following by Turkey, Iran and Russia.
Keywords: Triple Helix, university, Industry, Government, Innovation
Introduction
In present societies, knowledge is known as the main source of Economic prosperity and
Societies that derive their economical power from the production and diffusion of information
and knowledge are referred to as knowledge-based societies or economies (Foray &
Lundvall,1996). Knowledge-based societies have a well-established knowledge infrastructure
which works as an engine for organized novelty production and innovation to occur (Khan et al.,

2. 2011). In fact, the production of knowledge is a necessity but isn‟t sufficient for innovation. It
creates a potential which can be actualized by bringing together users, producers, entrepreneurs,
and policy-makers in a “transaction space” where problems and possibilities can be argued and
traded-off (Nowotny et al., 2001). Etzkowitz and Leydesdorff (2000) also argued that
communication and interaction between government, industry and academia are essential
elements of the innovation system. Innovation system is conceivable in some kind including the
National Innovation System, mode1 and mode2 knowledge, triple helix model (Khan and Park,
2011). Triple Helix of university, industry, government relationships in the last years has
attracted a lot of attentions As far as an annual conference with the same name formed and in the
Science Citation Index, there are nearly 300 articles in this field (Meyer et al., 2003). Dzisah and
Etzkowitz (2009) emphasized that the TH of UIG joint projects makes it possible to stimulate the
knowledge-based strategy and speed the rate of socioeconomic development by enhancing the
free flow of people, ideas and innovations in the national S&T capacity of R&D systems. The
Triple Helix concept has also been used as an operational strategy for regional development and
to further the knowledge-based economy in Sweden (Jacob, 2006) and Ethiopia (Saad et al.,
2008) and recently Amsterdam has been adopted it as practical model of economic development
(Leydesdorff, 2012). Nevertheless however, in international literatures, this model has received
less attention in Asia context (Khan et al., 2011). Since the triple helix model provides a
conceptual framework for evaluating the knowledge base development (Leydesdorff &
Etzkowitz, 2001) This paper, using the Webometrics techniques, studies university, industry and
government relation in selected countries, the Netherlands, Russia, Turkey and Iran.
Theoretical Framework

3. There are several approaches to understanding the complex nature and behavior of the
components involved in the production and dissemination of knowledge in the community
(Gibbons et al,. 1994). Etzkowitz and Leydesdorff proposed Triple Helix and so mentioned faced
with great attention.
Triple Helix
Triple Helix network analysts argue that UIG interactions represent the core of knowledge-based
innovation with circulation among and within the three spheres (Park & Leydesdorff, 2010).
These interactions form an overlay that develops synchronously with development of tree section
of the system. In fact, Etzkowitz and Leydesdorff (2000) argued this overlay as a dynamic
subsystem. The system acts in transdisciplinary way and is able to translate academic creativity
to application without determination of integration of each of component. This process may blur
boundary of institutions and create the new form of innovation systems. The common objective
is to realize an innovative environment consisting of university spin-off firms, tri-lateral
initiatives for knowledge-based economic development, and strategic alliances among firms
(large and small, operating in different areas, and with different levels of technology),
government laboratories, and academic research groups. These arrangements are often
encouraged, but not controlled, by government Despite of bilateral, in trilateral in which one
string can relate to each others, an overlay of connections, networks and organizations inter
strings is formed. The sources of innovation in a Triple Helix configuration are no longer
synchronized a priori. They do not fit together in a pregiven order, but they generate puzzles for
participants, analysts, and policy-makers to solve. This network of relations generates reflexive
subdynamics of intentions, strategies, and projects that add surplus value by reorganizing and
harmonizing continuously the underlying infrastructure in order to achieve at least an

4. approximation of the goals. The issue of how much we are in control or non-control of these
dynamics specifies a research program on innovation (Park & Leydesdorff, 2010). Briefly, the
Triple Helix model enables us to consider empirically dynamics (e.g., synergies) among the three
components (Leydesdorff, 2012).
Measuring knowledge based innovation system
Triple Helix connections can be measured by variables such as budget, collaboration and
citation. The mutual information in the three dimensions of the Triple Helix enables us to
measure networks at each moment in time in terms of probability distributions and to evaluate
the measurement results in terms of the dynamics (Leydesdorff, 2009). Describing network as a
Probability distribution, enable us to use Shanon communication Theory (1948). The expected
information content of the message that these events have happened with this observed
frequency distribution, can be expressed in terms of bits of information using the Shannon-
formulas (Leydesdorff et al., 2012):
Txyz= Hx + Hy + Hz- Hxy- Hxz- Hyz+ Hxyz
The uncertainty of measured variables in each of component is reduced at the system‟s level by
the relations at the interfaces between them, but the three-dimensional uncertainty adds
positively to the uncertainty that prevails. Negative values show reduce of uncertainty and
increase in interactions (Leydesdorff, 2009).
Methods
This research is based on Webometrics methods. We performed this research in two ways:

5. 1. Researchers introduced a technique for evaluating Triple Helix in web (Leydesdorff, 2000).
The main idea is using hits number for University, Industry and Government and any of their
combinations in national domain for each country. We used these words for countries:
Netherland: universiteit, industrie, overheid.
Russia: иве и е , ш е , ави е в .
Turkey: üniversite, sanayi, hükümet.
Iran: ‫,دانشگاه‬ ‫,صنعت‬ ‫.دولت‬
So argued Leydesdorff (2003) this method has its shortcomings, but so we told this method used
by a group of researchers.
2. We confined our search to Rich Files. The Rich Files in this research are DOC, PDF and PPT
and we used these files because are the most dominant type of scientific production and in some
paper we named it “Scientific presence in Web”(Nourmohammadi and Keramatfar, 2014). For
example:
site:ir filetype:pdf OR filetype:doc OR filetype:ppt ‫دانشگاه‬ AND ‫صنعت‬ AND ‫دولت‬
For Iranian co-occurrence of “University”, “Industry”, “Government” in Reach Files.
In fact this method is a combination of Scientometrics and Webometrics methods that used for
studying Triple Helix, in one hand researchers used co-occurrence in scientific indexes such as
WOS and in other hand used it in Web, and we combined them.

6. Netherlands Was selected because one of the most famous researchers of this field belong to it
and so mentioned Amsterdam has adopted Triple Helix as practical model for its economic
development so it is a yardstick for this research. Russia was selected because based on Scimago
it was in sixteen in the world in 2012 and Iran was seventeen. Also this paper is prepared for the
Triple Helix 2014 at Russia. Turkey was selected because it is the regional rival of Iran in
science and technology. We used Google and the time span was 2004-2013 and Data gathered in
1 of May 2014.
Findings
1. Measuring Triple helix based on co-occurrence in Web
Figure1 shows the Google estimation of the hits number of words and their combinations. So
Park et,.al(2005) mentioned, “University” is the most common word and it shows web scientific
function. Figure1A shows that for “university” word, all countries had a relative equal position,
but this situation changed with increase in Turkey, Iran and Russia and decrease in Netherlands.
Figure 1B shows that “Industry” word in Netherlands and Russia from 2009 decreased but in
later years it increased in all countries, in 2013 Iran is the highest. “Government” was increased
slowly, but in recent years its rate increased. Industry is weakly represented in this data that
agree with Leydesdorff results (2003).

7. A. university
B. industry
C. government
0
200,000
400,000
600,000
800,000
1,000,000
1,200,000
2005 2006 2007 2008 2009 2010 2011 2012 2013
netherland Russia Turkey Iran
0
100,000
200,000
300,000
400,000
500,000
2005 2006 2007 2008 2009 2010 2011 2012 2013
netherland Russia Turkey Iran
0
200,000
400,000
600,000
800,000
2005 2006 2007 2008 2009 2010 2011 2012 2013
netherland Russia Turkey Iran

8. D. university AND industry
E. university And government
F. industry AND government
0
100,000
200,000
300,000
400,000
2005 2006 2007 2008 2009 2010 2011 2012 2013
netherland Russia Turkey Iran
0
100,000
200,000
300,000
400,000
2005 2006 2007 2008 2009 2010 2011 2012 2013
netherland Russia Turkey Iran
0
100,000
200,000
300,000
400,000
2005 2006 2007 2008 2009 2010 2011 2012 2013
netherland Russia Turkey Iran

9. G. university AND industry AND government
Figure1. Number of hits for Triple Helix combinations
In bilateral combinations, the most common is “University AND Government”, Figure1D,E,F,G
show these combinations for selected countries. “university AND industry” is the most dominant
in Turkey. but “university And government” is more dominant in Iran and Netherland. it agree
with Jowkar And Osareh (2014) that observed this bilateral most dominant in Iran by
Scientometrics approach.
0
100,000
200,000
300,000
2005 2006 2007 2008 2009 2010 2011 2012 2013
netherland 36,800 Turkey Iran

10. Figure2.Value of Triple Helix in Netherlands, Russia, Turkey, Iran based on Web
Figure2 shows that Triple Helix measure in Netherlands is better than other countries, in other
word, “university”, “Industry” and “Government” are more integrated in Netherlands. Turkey
has a slow decrease. Russia from 2010 has stared to a quick increase. In compression Russia
against Netherlands, these results agree to with Leydesdorff (2003) experiment that was based on
WOS data. Iran has had a relatively fixed trend until 2012. In 2012 is in the worse situation and
after that has started to increase.
2. Measuring Triple Helix based on co-occurrence in Reach Files
Figure3 shows the Google estimation of the hits number of words and their combinations in Rich
Files. Also in this case “University” is the most common word. Unlike to previous section,
number of hits in Rich Files is dispread for countries. Here in all words, except “government”
Russia is higher than other countries. Unlike the previous, here the “government” is weak.
-0.5
-0.45
-0.4
-0.35
-0.3
-0.25
-0.2
-0.15
-0.1
-0.05
0
2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014
nl
ru
tr
ir

11. A. university
B. industry
C. government
0
50000
100000
150000
200000
2005 2006 2007 2008 2009 2010 2011 2012 2013
netherland Russia Turkey Iran
0
50000
100000
150000
200000
2005 2006 2007 2008 2009 2010 2011 2012 2013
netherland Russia Turkey Iran
0
50000
100000
2005 2006 2007 2008 2009 2010 2011 2012 2013
netherland Russia Turkey Iran
0
10000
20000
30000
40000
2005 2006 2007 2008 2009 2010 2011 2012 2013
netherland Russia Turkey Iran

12. D. university AND industry
E. university And government
F. industry AND government
G. university AND industry AND government
Figure3. Number of hits for Triple Helix combinations in Rich Files
0
10000
20000
30000
40000
2005 2006 2007 2008 2009 2010 2011 2012 2013
netherland Russia Turkey Iran
0
10000
20000
30000
40000
2005 2006 2007 2008 2009 2010 2011 2012 2013
netherland Russia Turkey Iran
0
10000
20000
30000
2005 2006 2007 2008 2009 2010 2011 2012 2013
netherland Russia Turkey Iran

13. “university AND industry” is the most dominant in Netherland and Turkey but “university And
government” became dominant in Iran and Russia in last year.
Figure4 shows that Triple Helix measure in Netherlands is better than other countries, in other
word, “university”, “Industry” and “Government” are more integrated in Netherlands and this is
In accordance with previous section but there is a decrease in values for this country. But Turkey
has a slow increase in this way. Russia shows the obvious difference, it has a slow increase but,
its position is lower than the previous. Iran has had a relatively fixed trend but it is lower than the
previous section. For comparison of two methods we examine a correlation test and this test
shows that there is not a significant correlation between two methods for any of these countries.
Figure4. Value of Triple Helix in Netherlands, Russia, Turkey, Iran based on Rich Files
Conclusion
This paper aimed to measure Triple Helix for studying the innovation infrastructure in Iran in
compare with some countries. We used two resources; first the web (such as other studies e.g
-0.6
-0.5
-0.4
-0.3
-0.2
-0.1
0
2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014
netherland
Russia
Turkey
Iran

14. Leydesdorff (2003)), second we used Rich Files as Scientific publication in web. In first
resource; the results showed that in selected countries, “University”, “Industry” And
“Government” are more integrated in Netherlands. Iran in compare with other countries has no a
good situation. This result agrees with Jowkar And Osareh (2014) that studied Triple Helix in
Iran based on Scientometrics method. In compare with Netherlands as yardstick, Iran is very
weak base on this indicator. In compare with Turkey, Turkey has a better situation in all time but
the distance increased recently. In compare with Russia, Russia only in 2010-2011 has had a
worse situation than Iran but it recently increased and in 2013 it approached to Netherlands. In
second resource; the results show a different situation. Netherlands has higher value in this
indicator, following by Turkey, Iran and Russia, it agrees with Leydesdorff et.al. (2013) that
concluded the Russian economy is not knowledge base. For policymakers, inappropriate
communications of “university”, “Industry” and “Government” has Became apparent. In fact,
nevertheless of quantitative development in scientific production, Regardless of their quality,
Due to the lack of proper innovation infrastructure, we should not to expect effectiveness. Using
of this indicator for evaluation in longitudinal will result to integration in “university”,
“Industry” and “Government”.
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