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Does regional innovation occur across geographical boundaries?Examining university-industry linkage in South Korea using a mixed method 2011. 4. 2. Ki-Seok Kwon, SeolahKIM & Han Woo PARK
Contents
I. Introduction
Introduction Importance of the exploitation of university research has echoed academia as well as policy communities To find the effective U-I condition, a great number of researches have been carried out - the relationship between the internal (e.g. size and legal status) and external (e.g. location and industrial background) characteristics of the two actors (i.e. universities and firms) and their knowledge transfer activities
Introduction Basically, the university-industry linkage can be regarded as a part of network of innovation actors. However, few studies have directly applied social network analysis (Van DerValk et al., 2010) Different from the strong research universities in developed countries (e.g. MIT and Stanford University), Korean universities’ academic research has been hardly connected to industrial innovation (Eom &Lee, 2010).
Geographical proximity of university to industry and universities’ KT activities The U.S. universities located in a region with a concentration of high-tech industry are more likely to be involved in knowledge-transfer activity (Friedman &Silberman, 2003) The companies closer to universities are more likely to provide R&D funding to the universities in the U.S (Mansfield & Lee,1996)
Geographical proximity of university to industry and universities’ KT activities Based on a significant positive correlation between the R&D expenditure of the US universities and patenting activity of local firms at state level, Jaffe (1989) focuses on the localised knowledge-spillover activities of universities In a German case, Audretsch et al. (2004) confirm that geographical proximity is an important factor for human resource flow between university and industry
II. Method
Method – a mixed approach In 2007, total of 2,395 faculty members across sixteen Korean provinces including metropolitan areas took part in the survey  Social network analysis : this study more focuses on the link (i.e. university-industry linkages) and the characteristics of nodes (i.e. gender, age and geographical location) of two actors
III. Results
Intra- and Inter-provincial U-I Collaboration in 16 Regions in South Korea
R&D Expenditure Rate by Sector of Performance and Region in 2007 Source: data based on MEST (2008), Survey of Research and Development in Korea 2008, Korean Ministry of Education, Science and Technology.
Korean Universities’ and Firms’ R&D Expenditure Rate and their degree of internal collaboration in 16 Regions in 2007
Structure of Inter-provincial Collaboration Network using a Circle Lay-out Algorithm
V. Discussion and Summary
Discussion and Summary Seoul and Gyunggi are identified as central nodes. That is, the academics in other regions tend to collaborate with firms in this region. The rich resource condition such as R&D expenditure can be an explanation (Shaprio et al., 2010). However, the other regions such as Jeju and JeonbukDagu with a relatively small amount of R&D expenditure have shown a strong intra-collaboration. In addition to the central hub of the network, we also identified several peripheral clusters grounded upon the geographical proximity
Discussion and Summary However, we have not yet analysed the types of channel (e.g. consulting, exchange of personals and co-operative research) in the network. In a final version of this paper, we expect to delineate a network with richer information by adding these factors to the analysis of the network.
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Does regional innovation occur across geographical boundaries

  • 1. Does regional innovation occur across geographical boundaries?Examining university-industry linkage in South Korea using a mixed method 2011. 4. 2. Ki-Seok Kwon, SeolahKIM & Han Woo PARK
  • 4. Introduction Importance of the exploitation of university research has echoed academia as well as policy communities To find the effective U-I condition, a great number of researches have been carried out - the relationship between the internal (e.g. size and legal status) and external (e.g. location and industrial background) characteristics of the two actors (i.e. universities and firms) and their knowledge transfer activities
  • 5. Introduction Basically, the university-industry linkage can be regarded as a part of network of innovation actors. However, few studies have directly applied social network analysis (Van DerValk et al., 2010) Different from the strong research universities in developed countries (e.g. MIT and Stanford University), Korean universities’ academic research has been hardly connected to industrial innovation (Eom &Lee, 2010).
  • 6. Geographical proximity of university to industry and universities’ KT activities The U.S. universities located in a region with a concentration of high-tech industry are more likely to be involved in knowledge-transfer activity (Friedman &Silberman, 2003) The companies closer to universities are more likely to provide R&D funding to the universities in the U.S (Mansfield & Lee,1996)
  • 7. Geographical proximity of university to industry and universities’ KT activities Based on a significant positive correlation between the R&D expenditure of the US universities and patenting activity of local firms at state level, Jaffe (1989) focuses on the localised knowledge-spillover activities of universities In a German case, Audretsch et al. (2004) confirm that geographical proximity is an important factor for human resource flow between university and industry
  • 9. Method – a mixed approach In 2007, total of 2,395 faculty members across sixteen Korean provinces including metropolitan areas took part in the survey Social network analysis : this study more focuses on the link (i.e. university-industry linkages) and the characteristics of nodes (i.e. gender, age and geographical location) of two actors
  • 11. Intra- and Inter-provincial U-I Collaboration in 16 Regions in South Korea
  • 12. R&D Expenditure Rate by Sector of Performance and Region in 2007 Source: data based on MEST (2008), Survey of Research and Development in Korea 2008, Korean Ministry of Education, Science and Technology.
  • 13. Korean Universities’ and Firms’ R&D Expenditure Rate and their degree of internal collaboration in 16 Regions in 2007
  • 14. Structure of Inter-provincial Collaboration Network using a Circle Lay-out Algorithm
  • 15. V. Discussion and Summary
  • 16. Discussion and Summary Seoul and Gyunggi are identified as central nodes. That is, the academics in other regions tend to collaborate with firms in this region. The rich resource condition such as R&D expenditure can be an explanation (Shaprio et al., 2010). However, the other regions such as Jeju and JeonbukDagu with a relatively small amount of R&D expenditure have shown a strong intra-collaboration. In addition to the central hub of the network, we also identified several peripheral clusters grounded upon the geographical proximity
  • 17. Discussion and Summary However, we have not yet analysed the types of channel (e.g. consulting, exchange of personals and co-operative research) in the network. In a final version of this paper, we expect to delineate a network with richer information by adding these factors to the analysis of the network.
  • 18. Q & A