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.,

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

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

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:

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: ÜÖивеëïиöеö, äëܽ▲ш¿еÖÖÜïöá, äëавиöе¿áïöвÜ.

Turkey: üniversite, sanayi, hükümet.

Iran: دولت ,صنعت ,دانشگاه.

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.

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).

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

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

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

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

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

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

“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

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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