Progress Report:Triple Helix (TH) on Web&Types of TH Gohar Feroz Khan Dept. of Media & Communication, YeungNam University,South Korea. Prepared for: SSK (Social Science Korea) Project Workshop Busan
Introduction Progress Report Article 1: Measuring Triple Helix on the web. Longitudinal trends of among University (U), Industry (I), and Government (G) Article 2: Broadening TH by proposing 5 types of TH That may exist under certain conditions from evolutionally economic point of view We will use Social network analysis concepts such as strong and week ties and information theory.
Article 1Measuring Triple-Helix on the Web: Longitudinal Trends of Relationship among University-Industry-Government (UIG) in Korea
Article 1: Measuring TH on the web Several models and approaches have been proposed for measuring knowledge-based system of innovation, for example National Innovation System (Freeman, 1987, 1988; Lundvall; 1988). Mode 1 and Mode 2 knowledge creation Machanisim (Gibbon, 1994) Triple Helix Model (Etzkowitz & Leydesdorff, 1995, 2000)
However, majority of the studies that measure this infra are conducted in non-Asian (i.e. English) context (LEE and JEONG (2008) And limited only to analyzing contents of written communication in English. In addition, they use well documented and formal written communications, such as, patent and publications, for example PARK et al. (2005). Furthermore, most of the knowledge-based innovation indicators, such as, Science Citation Index are available commercially and accessibly only to subscribers
Thus In this research, we try to measure the strength of relations among TH components in Korean context using World Wide Web (WWW). We argue that WWW and advanced search engines on the internet can indicate UIG relations using Triple helix indicators (Leydesdorff and Curran, 2000;) in Korean context
Method We employed webometrics combined with content analysis, and co-word analysis technique in this research. Data: Naver.com (the most popular search engine in South Korea) using WeboNaver in March 2010 Naver started its service in 1998, thus we harvested the data from 1999 to 2009 (see table 1) We analyzed a verity of sources—web, documents, blogs, online café, knowledge in, and media Search Terms with Boolean operators: “대학(dae-hawg)” “기업(ghi-oeup)” and “정부(Jeong-bu)” were used.
Table 1 Number of hits for TH components from 1999 to 2009
Results Figure 1 A longitudinal trend of Web-based T(uig) across categories
Results Figure 2 Occurrence of UIG in Web documents Figure 3 Strength of the bilateral and trilateral relationship in web docs President Noh—2003 to 2007
Results Figure 4 and 6 Titles of Knowledge In
Results Figure 6. A longitudinal trend of occurrence of U, I, G in the titles of all five categories
Conclusion The results indicate that the UIG relationship varied according to the government’s policies and that there was some tension in the longitudinal UIG relationship. Further, websites/documents and blogs were the most reliable sources for examining the strength of and variations in the UIG bilateral and trilateral relationships on the Web. In addition, web-based T(uig) values showed a stronger trilateral relationship and larger variations in the UIG relationship than SCI-based T(uig) values.
Article 2Broadening the Triple Helix
Introduction We have several models National Innovation System (Freeman, 1987, 1988; Lundvall; 1988). Mode 1 and Mode 2 knowledge creation Machanisim (Gibbon, 1994) Triple Helix Model (Etzkowitz & Leydesdorff, 1995, 2000) According to Etzkowitz & Leydesdorff (2000) knowledge-based innovations system can be operationalized in terms of network of relationships between university, industry, and government
Introduction However, TH fails to capture the dynamic of nature of knowledge-based innovation (KBI) system that may prevail in different economies (particularly developing countries) under the pressure of economic condition from evolutionary perspective. In this article, we argue that interaction among the actors of knowledge based innovation system is a complex phenomenon & may take different forms due to economic pressure, prevailing circumstances, diversity in the linkages, and complex nature of KBI system
Social Network Ties Strength of Week ties (Granovetter,1973) Bridging ties (Harary, et al, 1965;) Structural holes (Burt, 1992)
5 types of TH Type 1: Figure 1 Type 1 Triple Helix University (U) Industry (I) Type 1 TH may exist in situation where the fundamental components (university, industry, government) of a knowledge-based economy produce novelty independently from one another and networked ties are not yet established. Lack of network ties; KBI system may exist but no collaborative novelty production is taking place, thus it is inefficient Government (G) Let us assume that U represents the novelty produced by university, expressed in terms of SCI publications, I by industry, and G by government independently from one another. The total output of the knowledge based innovation system “T” can be expressed as T= U+I+G
5 types of TH Type 2: Figure 1 Type 1 Triple Helix University (U) Industry (I) Government (G) Type 2 TH exists when two of the components of KBI system established bilateral ties for join novelty production. However the third component is not yet part of network as shown in the figure 2. Here U and G are collaborating in novelty production whereas; I is not part of network and may produce novelty independently. Network ties established; KBI exist but not efficient due “I” not participating in the systems. Missing ties. One of the fundamental components is not participating in the novelty production Figure 2 Type 2 Triple Helix The total output of the knowledge based innovation system “T” can be expressed as T= U+I+G-ug
5 types of TH Type 3: Figure 1 Type 1 Triple Helix Government (G) University (U) Industry (I) Type 3 TH exists when one of the players, normally government, plays a central role in KBI system by facilitating the novelty production and different types of ties exist among the players, such as, combination of strong and week ties as shown in figure 3. Bridging , week ties, and structural hole KBI system established with high efficiency due to existence of combination of strong ties, week ties, and bridging ties. The total output of the knowledge based innovation system “T” can be expressed as T= U+I+G-ug-ig
5 types of TH Type 4: Figure 1 Type 1 Triple Helix Bridging , week ties, and structural holes missing Industry (I) University (U) When all the components of KBI system establish bilateral network ties among each other it forms type 4 TH as shown in the figure 4. Government (G) Network ties established; KBI exist but not efficient due to too many strong ties and information redundancy. Too costly to maintain this system Figure 4 Type 4 Triple Helix The total output of the knowledge based innovation system “T” can be expressed as T= U+I+G-ug-ig-ui
5 types of TH Type 5: Figure 1 Type 1 Triple Helix Bridging , week ties, and structural holes missing University (U) Industry (I) When all the components of KBI system establish bilateral and trilateral network ties among each other it forms type 5 TH as shown in the figure 5. Redundant network ties not efficient; may give birth to negative network externality. The KBI is complex and too costly to operate. Government (G) Figure 5 Type 5 Triple Helix The total output of the knowledge based innovation system “T” can be expressed as T= U+I+G-ug-ig-ui+uig
Empirical validation of TH types In future, we plan to use WoS data to show the existence of TH types. For example, we can use SCI publication longitudinal data of Korea and some other countries?