Peeling off the Layers on Knowledge Networks in terms of Collaboration and Communication Relations in the Systems of Innovation:  a case of South Korea
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Peeling off the Layers on Knowledge Networks in terms of Collaboration and Communication Relations in the Systems of Innovation: a case of South Korea

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• Invited speaker, Manchester Institute of Innovation Research, Manchester Business School, The University of Manchester, Manchester, United Kingdom, 17 February, 2009

• Invited speaker, Manchester Institute of Innovation Research, Manchester Business School, The University of Manchester, Manchester, United Kingdom, 17 February, 2009

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Peeling off the Layers on Knowledge Networks in terms of Collaboration and Communication Relations in the Systems of Innovation: a case of South Korea Presentation Transcript

  • 1. Knowledge-based national innovation system - A case of South Korea Dr. Han Woo PARK Visiting Research Fellow Oxford Internet Institute, UK Assistant Professor Department of Media & Communication YeungNam University 214-1 Dae-dong, Gyeongsan-si, Gyeongsangbuk-do 712-749 Republic of Korea [email_address] http://www.hanpark.net This is in collaboration with Min-Ho So, L. Leydesdorff, and M. Thelwall Virtual Knowledge Studio (VKS)
  • 2. Knowledge-based innovation
    • There are probably three ways to measure knowledge-based innovation system in terms of networked communication
    • Journal articles: Traditional knowledge indicator; Scientometric
    • Patent registration: Innovation indicator; Technometric
    • Website links: Digital (proxy) indicator; Webometric
  • 3. Knowledge-based systemness
    • A surprising growth of SCI publications with a Korean address
    • Korea increases its percentage world share of publications with approximately 0.20 percent point each year (r 2> 0.99). In terms of the number of SCI papers, Korea occupied the 14th position in the year 2005
    • Korea obtained even the 6 th position during the first eight months of the year 2004 in the field of nanotechnology
  • 4. Long-term trend of the percentage publications with a Korean address in the SCI
  • 5. Increasing Korean SCI journals
  • 6.  
  • 7. Korea’s portfolio becomes strong?
    • The answer is both yes and no
    • Why YES?
    • Research evaluation and scholarly practice become internationalized and national R&D budget is growing
    • WCU (World Class University) project
    • YES part is not the focus of this presentation
  • 8. Critical points and frustrating aspects
    • Only three scientists working in Korean institutions were included in the 2008 list of ISI’s Highly Cited Researchers
    • Korean SCI journals are being neglected by domestic/international scientists as a reference journal
    • - These journals function more like publication places, neither research channels nor information sources
  • 9. Position of Korean SCI journals?
  • 10. Networked innovation system
    • A knowledge-based innovation can no longer be attributed to single nodes in a society
    • New technologies enable individual and institutional actors to collaborate in new modes
    • Is Korea national R&D system strong in terms of networkedness?
  • 11. Gov’t policy and TH
    • The networked knowledge infrastructure can be measured in terms of a Triple-Helix of University-Industry-Government relations; L. Leydesdorff
    • Does Korea governmental policy facilitate the development of cooperation among individual/institutional actors comprising of national research system?
  • 12. Characteristics of R&D programs according to government Government Characteristics of R&D programs related to the TH indicators Park, Jung-Hee (1970-1979) Government’s strong push to run governmental institutes and joint research between universities and public organizations Chun, Doo-Hwan (1980-1987) Merger and acquisition among government-sponsored research institutes; e.g., the integration of the KAIS (Korea Advanced Institute of Science) university and the KIST (Korea Institute of Science and Technology) into the KAIST (Korea Advanced Institute of Science and Technology) Roh, Tae-Woo (1988-1992) The gradual opening of research organizations in both private and public sectors; e.g., KIST became independent from KAIST in 1989 Kim, Young-Sam (1993-1997) Dominance of governmental agencies from early 1990 to 1997 when Korea started to be subject to International Monetary Fund (IMF) conditions Kim, Dae-Jung (1998-2002) BK21 project started in 1999 to increase the research capacity of universities through large central government subsidies, thus decreasing UIG joint research Roh, Moo-Hyun (2003-2007) Continual promotion of the BK21 and internationalization of R&D, particularly in the academic sector
  • 13. Number of papers by Korean authors in the Science Citation Index and bi- and trilateral relations between TH-sectors within the economy
  • 14. Mutual information in bilateral relations between the TH sectors in Korea
  • 15. The Mutual Information in Two Dimensions : T ij = H i + H j - H ij T ij ≥ 0 The Mutual Information in Three Dimensions: T UIG = H U + H I + H G – H UI – H IG – H UG + H UIG T UIG is potentially negative A negative entropy can be a consequence of the mutual relations at the network level . The configuration then reduces the uncertainty.
  • 16. Mutual information in trilateral Triple Helix relations in Korea
  • 17. Have changes in government research policies affected longitudinal changes?
    • First, there is the reduction of uncertainty among academic, public, and industrial research actors in the Korean publication system from 1970 to 1990.
    • Second, the mutual information among the three TH agencies ( T uig) is relatively stable during the 1990s but begins to decrease over the last ten years. The trend line shows that the TH dynamics of UIG relations have varied considerably; this variation generally accords with changes in Korean government research policies.
  • 18. Publication patterns in and between TH sectors using the A&HCI Index
  • 19. Mutual information measured in bilateral relations between TH sectors using the SSCI
  • 20. Publication rates of Korean papers and synergy effects among TH sectors on the basis of coauthorship relations in the SSCI
  • 21. Relative position of Korea TH SCI 2002 Number UI UG IG UIG Univers Industry Govt All 683222 17095 116782 4626 5664 556370 41840 234843 USA 238676 7274 40650 1777 2732 206813 18193 68835 EU 250395 4586 54617 1400 2187 204531 11011 99830 UK 66544 1569 14263 360 763 53972 3617 26673 Germany 59630 1181 14986 405 703 50319 2925 24364 France 39973 431 12214 422 585 26663 1826 25721 Scand 30437 592 8757 170 411 26283 1431 13064 Italy 29795 374 7609 79 321 26680 956 10863 Netherlands 17865 328 4663 78 307 15927 859 6762 S. Korea 14931 533 3115 118 183 13163 996 4904 Japan 68338 4303 13297 1113 1481 57345 9892 22776 PR China 28913 381 6408 111 173 24328 728 11103 Taiwan 9572 183 2772 15 59 8608 295 3757 Singapore 3411 110 622 16 53 2978 202 1085 Russia 20723 81 6637 134 157 11486 443 15960 India 12570 109 2180 92 67 7140 459 7486 Brazil 10888 189 2054 45 81 9584 386 3368
  • 22. Source: Science Citation Index 2000 2002 -70.7 -71.0 -45.3 -54.0 -39.6 -42.5 -32.5 -27.6 -32.8 -82.4 -11.0 -18.0 -28.6 -33.7 -18.9 -67.7 -26.8
  • 23. Top 68 title words with cosine ≥ 0.1 for South-Korea Science Citation Index 2002 bio materials organic control medical Co-word network in Korea
  • 24. Top 49 words with cosine ≥ 0.1 for The Netherlands Science Citation Index 2002 cancer biotech Co-word network in the Netherlands
  • 25. Cosine normalized map of 105 co-occurring words in patents (in 2002) with a Dutch address among the assignees or inventors (N Patents = 2,824; Word frequency > 22; cosine ≥ 0.1).
  • 26. Cosine normalized map of 103 co-occurring words in patents (2002) with a Korean address among the assignees or inventors (N Patents is 4,200; Word frequency > 40; cosine ≥ 0.1).
  • 27. Cosine normalized map of 103 co-occurring words in patents (2002) with a Korean address among the assignees or inventors (N Patents is 4,200; Word frequency > 40; cosine ≥ 0.1). info devices coating chips display printing
  • 28. Inter-regional collaboration
    • Three kinds of data set among 16 Korean regions were constructed: Total number of publications, citations, cited articles
    • Network measures
    • Centrality: sum of connections
    • Density: cohesive properties
    • Fragmentation: to identify the key actor whose replacement is extremely urgent if the actor is excluded from the network
  • 29. Seoul’s (normalized) centralities and overall network centralization
  • 30. Summary of centrality analysis
    • In the last 10 years, the centrality of Seoul in the co-authorship network was clearly decreasing. peaked in 1990 at 34.38 and then decreased to a plateau
    • Attributed to the emergence of Dae-jeon and Kyeong-gi
    • The re-structuring of the two regions was obviously a result of government interventions
  • 31. Density values 1974-2006 for all categories, SCI-only, SSCI-only
  • 32. Summary of density analysis
    • The co-authorship networks of Korean provincials became more cohesive over the last three decades (0.004 in 1974 to 48.779 in 2006), revealing the rapidly increasing collaboration among geographically dispersed researchers and institutions.
    • Need to look at longitudinal trends of ‘clustering coefficient’ besides densities
  • 33. Fragmentation value when one key player, Seoul, is removed
  • 34. Summary of fragmentation analysis
    • Seoul was identified as the key player over the decades but NOT selected as the most important key player from 1992 to 1994
    • Dae-jeon was identified as the key player in 1992 and 1993 and Busan in 1994 in the co-authorship network
    • In the cited article network, Dae-jeon was chosen as the most powerful key player in 1992 and 1993 and Kwang-ju in 1994.
  • 35. Web indicator for knowledge and information networks
    • Links between sites might not provide for actual knowledge/information flow
    • But one university receives more links from another, this can be because it is more productive in terms of scholarly performance (e.g., journal article publications, class materials, pre-prints etc.)
    • Or two universities are more collaborative than ..
    • Indicator for quantity, not quality??
    • Hyperlinks tend to reveal both existing and emerging socio- c ommunication al network
  • 36. Universities in Eurasia (at least 100 hyperlinks)
  • 37. Universities in Asia (at least 20 hyperlinks)
  • 38. Universities in Asia (at least 50 hyperlinks)
  • 39. Summary of ASEM links
    • Clear geographic trends are visible, with most universities connecting mainly to other universities from the same country
    • A closed-network among China and Singaporean universities: Collaboration
    • Academic digital divide
    • European universities (e.g., UK) have more incoming links than Asian ones
  • 40. Discussion issues
    • Role of hyperlinks as an indicator of what?
    • Innovation activity
    • Scientific activity
    • Communicational activity
    • Proxy VS Actual
    • Comparable to citation
    Configurations may constrain the further TH developments at national system level by generating more uncertainty than can be managed by three TH actors - L. Leydesdorff
  • 41. The end
    • Thank you for listening, and thank you to my assistants (Ae-Jin Bae) and collaborators (Loet Leydesdorff, Min-Ho So, Mike Thelwall, Hyo Kim)
    • Han - Woo Park , Ph.D.
    • Email: hanpark 2020 @ gmail.com
    • Website: www.hanpark.net
    • Partially supported by a Korea Research Foundation Grant