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The evolution of South Korea’s innovation system: moving towards the triple helix model?

Abstract

The South Korea’s innovation system has been transformed in tandem with rapid economic growth over the last three decades. In order to explore the evolution process of the innovation system in Korea, this study examines the trends and patterns in collaboration activities among the triple helix actors, such as university, industry, and government (UIG), using co-patent data. The triple helix framework is employed to analyze innovation dynamics within the networks of the bi- and trilateral relations embedded in patent collaborations. The analyses focus on how the triple helix dynamics have been shaped and transformed in the course of development of the innovation system. The results reveal that collaboration activities among UIG largely increased across three developmental phases from 1980 to 2012. In the early periods, strategic R&D alliances between industry and government sector were set up to strengthen enterprises’ innovation capabilities. When the Korean large conglomerates, Chaebols, became a dominant driver of domestic innovation activities, the primary agents of the collaborations shifted from industry-government to industry-university. The network analysis shows that university-industry collaboration is the strongest within the triple helix in recent years, followed by industry-government relations and then UIG relations. The tripartite collaboration has emerged with the rise of entrepreneur universities, but its network has rather been weak and inactive. While Korea has experienced a transition from statist model to a triple helix, the full-fledged triple helix model has not been established yet.

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Notes

  1. 1.

    The triple helix thesis focuses on the path to the triple helix from two different standpoints, such as a statist model and a laissez-faire model. The former Soviet Union, France, and many Latin American countries exemplify the statist model of government coordinating industry and academia to promote technology development. The loosening of top-down control and devolving powers of the central government often precede changes in the classic statist regime and lead to the statist transition process. However, Sweden and the US exemplify the laissez-faire model, where a strong ideology of individualism and limited state intervention operates in practice. For example, the anti-trust regulations and strong individual entrepreneurship in the US and the tradition of academic freedom and institutional autonomy with strict separation between public and private spheres in Sweden formed a laissez-faire triple helix, consisting of separate institutional spheres, distinct institutional roles, and indirect relations among spheres. When there was an economic crisis, however, government came to play a more interventionist role through providing the rule of the game (e.g., the US Bayh-Dole Act) as well as tri-lateral initiatives (e.g., Vinnova in Sweden). Government’s changing roles were observed in the US from economic recession of the 1970s and Sweden in the 1990s made the transition to an interactive triple helix. Recently, the model of government seems to be placed at the midpoint between the interventionist model (direct innovation policies) and the laissez-faire model (indirect innovation policies) in both countries.

  2. 2.

    This study utilizes patent data from the KIPO over those from the United States Patent and Trademark Office (USPTO), because domestic patent data from the KIPRIS are easily accessible and contain abundant information of co-inventorship, compared to those from the USPTO. It is more suitable to analyze collaborative networks among UIG, covering a range of domestic patent applications jointly filed by various UIG actors.

  3. 3.

    The Korean search terms are in parentheses and the search was made by the author in November 2013. Previous studies used various search terms for UIG in the Korean context. For example, Choi et al. (2014) and Park and Leydesdorff (2010) classified universities, colleges, and their affiliated institutions as the university sector; those including the terms “incorporated,” “corporation,” and “hospital” were labeled as the industry sector; and national agencies and non-profit organizations were considered as the government sector. In this study, however, universities and their affiliated organizations, such as the technology licensing office, are identified as the university sector. The “company” (Huisa) is used as the search term for industry, because it is a more suitable term to search for industry patents at the KIPRIS. In this study, all patents where co-assignees names include at least one of 24 Korean GRIs are considered as those that are relevant for the government sector and then they are filtered out in all the patents found with the search term “research institute (Yeonguwon).”

  4. 4.

    The total number of joint patent applications filed by university, industry, and GRI is 18,097. The actual cases for industry-GRIs are 8151, those for industry-university are 8193, those for university-GRIs are 1675, and those for university-industry-GRI are 78.

  5. 5.

    An “Act on Special Measure for Promotion of Venture Business” was implemented in 1997 to assist venture companies in start-up production, financing, workforce, technology, facilities, plant sites, and so on.

  6. 6.

    Based on the revision of Korean patent law in 2000, university and GRIs were entitled to a 50 % reduction of patent application fees and a 70 % reduction for individual inventors and SMEs until around the mid-2000s. Additionally, the average period of patent examination was reduced from 37 months in 1995 to 15 months in 2005.

  7. 7.

    The density is described as the proportion of collaboration ties in the network relative to the total number of all possible collaboration ties. If the number of nodes in a network is denoted as K and the number of total edge is denoted as L, then the density of the overall network (D) would be defined as follows: \(D = \frac{L}{{{{K(K - 1)} \mathord{\left/ {\vphantom {{K(K - 1)} 2}} \right. \kern-0pt} 2}}}\) The number between zero and one indicates the degree of how interconnected the actors are in the network. In this study, the density of most networks was found to be very low in that its value was almost close to zero across all periods. Network density usually shows the extents to which networks contain many ties between actors that is presumably cohesive with a tight structure. However, density may not be useful to measure the structural cohesion of the network, because it depends on the size of the overall network: thus, the larger the network, the lower the density. In this respect, mean degree centrality of all actors can be a better measure of overall cohesion than density, since it may not be influenced by network size and comparable between networks of different sizes (Nooy et al. 2005: 64).

  8. 8.

    Centralization measures the extent to which an entire network is centered on one or a few certain actors. If the centrality score of the most central actor is denoted as C* and that of each actor is denoted as Ci, centralization measure (C) can be calculated from \(C = \frac{{100\, \times \,\sum (C^{*} - Ci)}}{{{\text{MAX}}\sum (C^{*} - Ci)}}\).

  9. 9.

    The ETRI has the highest scores of all three centrality measures: degree centrality, closeness centrality, and betweenness centrality. Closeness centrality measures how closely an actor is related to others and easily obtains and spreads information. Closeness centrality of a vertex is calculated as the number of other vertices divided by the sum of all distances between the vertex and all others (Nooy et al. 2005). Betweenness centrality shows the extent to which an actor lies on the shortest paths between other pairs of actors in the network and estimates its influences and powers to others. Betweenness centrality measure can be calculated as the proportion of all shortest paths between pairs of other vertices that include the vertex.

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Acknowledgments

This research is funded by the Science and Technology Policy Institute. The author is very grateful for the valuable comments and suggestions of the anonymous reviews.

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Correspondence to Jungwon Yoon.

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Yoon, J. The evolution of South Korea’s innovation system: moving towards the triple helix model?. Scientometrics 104, 265–293 (2015). https://doi.org/10.1007/s11192-015-1541-6

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Keywords

  • Co-patent
  • Innovation systems
  • Triple helix
  • University-industry-government relations
  • Collaboration network
  • South Korea