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- 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”. References: Khan, G. F., Moon, J., & Park, H. W.Measuring Triple Helix on the World Wide Web, presented at presentation at Triple Helix 9 International Conference (Stanford University, 11-14 July 2011). Nowotny, Helga, Peter Scott, and Michael Gibbons (2001) Re-Thinking Science: Knowledge and the Public in an Age of Uncertainty. Cambridge: Polity Press.
- 15. Khan, G. F., Moon, J., & Park, H. W.Measuring Triple Helix on the World Wide Web, presented at presentation at Triple Helix 9 International Conference (Stanford University, 11-14 July 2011). Nowotny, Helga, Peter Scott, and Michael Gibbons (2001) Re-Thinking Science: Knowledge and the Public in an Age of Uncertainty. Cambridge: Polity Press. Khan, G. F., & Park, H. W. (2011). Measuring the triple helix on the web: Longitudinal trends in the university‐industry‐government relationship in Korea. Journal of the American Society for Information Science and Technology, 62(12), 2443-2455. Meyer, M., Grant, K., Morlacchi, P., & Weckowska, D. (2013). Triple Helix indicators as an emergent area of enquiry: a bibliometric perspective. Scientometrics, 1-24. Foray, D., & Lundvall, B.-A. (1996). The knowledge-based economy: From the economics of knowledge to the learning economy. In D. Foray & B.-A. Lundvall (Eds.),Employment and growth in the knowledge-based economy(pp. 11–32). Paris: OECD. Nowotny, H., Scott, P., & Gibbons, M. (2001).Re-thinking science: Knowledge and the public in an age of uncertainty. Cambridge: Polity Press. Etzkowitz, H., & Leydesdorff, L. (2000). The dynamics of innovation: From National Systems and „„Mode2‟‟ to a Triple Helix of university–industry–government relations.Research Policy, 29(2), 109–123. Dzisah, J., & Etzkowitz, H. (2009). Triple Helix Circulation: The Heart of Innovation and Development. A theme paper presented at the 2009 Triple-Helix annual conference. Glasgow, UK, 16-18 June 2009. Jacob, M. (2006). Utilization of social science knowledge in science policy: Systems of Innovation, Triple Helix and VINNOVA. Social Science Information, 45(3), 431-462. Saad, M., Zawdie, G., & Malairaja, C. (2008). The triple helix strategy for universities in developing countries: the experiences in Malaysia and Algeria. Science and Public Policy, 35(6), 431-443. Almeida, M. (2005). The evolution of the incubator movement in Brazil. International Journal of Technology and Globalisation, 1(2), 258-277. Leydesdorff, L., & Etzkowitz, H. (2001). The transformation of university-industry-government relations.
- 16. Leydesdorff, L., Perevodchikov, E., & Uvarov, A. (2013). Measuring Triple-Helix Synergy in the Russian Innovation Systems at Regional, Provincial and National Levels. arXiv preprint arXiv:1310.3040. ETZKOWITZ, H., Leydersdorff, L., & Van den Besslaar, P. (1994). Evolutionary economics and chaos theory: New directions in technology studies. Evolutionary economics and chaos theory: New directions in technology studies. Etzkowitz, H., & Leydesdorff, L. (2000). The dynamics of innovation: from National Systems and “Mode 2” to a Triple Helix of university–industry–government relations. Research policy, 29(2), 109-123. Gibbons, M., Limoges, C., Nowotny, H., Schwartzman, S., Scott, P., & Trow, M. (1994). The new production of knowledge: the dynamics of science and research in contemporary societies. London: Sage. Shannon, C. E. (1948). A mathematical theory of communication. technical journal. AT & T Bell Labs. Leydesdorff, L. (2012a). The Triple Helix, Quadruple Helix,…, and an N-Tuple of Helices: Explanatory Models for Analyzing the Knowledge-Based Economy? Journal of the Knowledge Economy, 3(1), 25-35; doi: 10.1007/s13132-13011-10049-13134. Leydesdorff, L. (2009). The communication of meaning in anticipatory systems: A simulation study of the dynamics of intentionality in social interactions. In other words, 5(5b), 5c. Leydesdorff, L. & Curran, M., (2000). Mapping university-industry-government relations on the Internet: the construction of indicators for a knowledge-based economy, Cybermetrics, 4. Available: http://www.cindoc.csic.es/cybermetrics/articles/v4i1p2.html Leydesdorff, L. (1995). The Triple Helix--University-industry-government relations: A laboratory for knowledge based economic development. Easst Review, 14(1), 14-9. Leydesdorff, L. (2006). The knowledge-based economy: Modeled, measured, simulated. Boca Raton, FL: Universal Publishers. Park, H. W., Hong, H. D., & Leydesdorff, L. (2005). A comparison of the knowledge-based innovation systems in the economies of South Korea and the Netherlands using Triple Helix indicators. Scientometrics, 65(1), 3-27. Jowkar, T., Osareh, F. (2014). Flow of Scientific Publications in Iran during 2007 to2011,
- 17. Based on Triple Helix of University, Industry and Government. Iranian Research Institute Iranian for Science and Technology. 29(2), 505-533. Kharazmi, O. A. (2010, October). Transfer of Technology from Iranian Universities to Industry: University Perspective. In VIII Triple Helix International Conference on University, Industry and Government Linkages. Kharazmi, O. A. (2010, October). Transfer of Technology from Iranian Universities to Industry: University Perspective. In VIII Triple Helix International Conference on University, Industry and Government Linkages. Nourmohammadi H, Keramatfar A. 2014. The relation between the number of countries-Rich Files on the web and countries-economic development. International Journal of Management and Humanity Sciences, Vol. 3, No. 6.