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The scientific impact and partner selection in collaborative research at Korean universities

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Abstract

This study seeks to bridge the gap between scientometrics literature on scientific collaboration and science and technology management literature on partner selection by linking scientists’ collaborator preferences to the marginal advantage in citation impact. The 1981–2010 South Korea NCR (National Citation Report), a subset of the Web of Science that includes 297,658 scholarly articles, was used for this research. We found that, during this period, multi-author scientific articles increasingly dominated single-author articles: multi-university collaboration grew significantly; and the numbers of research publications produced by teams working within a single institution or by a single author diminished. This study also demonstrated that multi-university collaboration produces higher-impact articles when it includes “Research Universities,” that is, top-tier university schools. We also found that elite universities experienced impact degradation of their scientific results when they collaborated with lower-tier institutions, whereas their lower-tier partners gained impact benefits from the collaboration. Finally, our research revealed that Korean universities are unlikely to work with other universities in the same tier. This propensity for cross-tier collaboration can be interpreted as strategic partner selection by lower-tier schools seeking marginal advantage in citation impact.

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Notes

  1. Research collaboration is also regarded as being useful from a technological perspective: for example, the quality and value of patents are positively influenced by research collaboration (Lee 2008).

  2. Jones et al. (2008) found that American universities are likely to collaborate within their own tier. They refer to these tendencies as the social stratification in multi-university collaboration and showed that the stratification has increased over time.

  3. When seeking out possible partners for scientific alliances, one may take some factors into consideration such as scientific specialty (Frenken 2002), national characteristics (Gazni et al. 2012), institutional differences (Leydesdorff and Sun 2009), physical distance (Hoekman et al. 2010; Katz 1994), and linguistic border effects (Narin et al. 1991). Since our sample is restricted to universities in a single nation, most of these factors, with the exception of scientific specialty, can be excluded from analysis.

  4. The 1981–2010 South Korea NCR also contains articles from social science, arts, and humanities disciplines. For the sample used in this study, however, the portion of the database comprised of these fields is insignificant. Therefore, we used only science and technology disciplines, which comprise 97.78 % of total papers. This portion is believed to be representative of the knowledge production of Korean universities.

  5. In the science and technology management literature, many alliance structure issues are investigated from a dyadic perspective. Gulati (1998) outlined the study of strategic alliances.

  6. The rate ratio and other effect size measures are thoroughly explained by Fleiss and Berlin (2009). In the health sciences, the ratio of two probabilities is referred to as the risk ratio or relative risk.

  7. Note that repeating for 1999 iterations leads to simple calculations of confidence intervals for common significance levels, e.g. 95 % (Carpenter and Bithell 2000).

  8. The probabilities of high impact for between-school collaboration with lower tiers are 0.31, 0.30, and 0.29 at tiers II, III, and IV, respectively. These values are greater than numbers for within-school collaboration (0.30, 0.28, and 0.25, respectively).

  9. These factors potentially influencing citation counts are stressed by prior research. Waltman et al. (2011) control for the effects of research fields and year in calculating indicators of citation impact. The number of authors is also regarded as a positive predictor for highly cited papers (Adams et al. 2005; Franceschet and Costantini 2010). Therefore, citation-based studies are likely to consider all these differences for obtaining specific influences.

  10. This finding is contrary to that of investigation by Jones et al. (2008) that US universities gain stronger marginal impact from between-school collaboration than they acquire from inside-school teamwork. This difference inspired us to investigate the reasons behind Korean university schools’ collaborative research.

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Acknowledgments

This research was jointly supported by: Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Science, ICT & Future Planning (2012R1A1A1013071); the BK21 PLUS through the National Research Foundation of Korea (NRF) funded by the Ministry of Education; ICT R&D Program 2013 funded by the Ministry of Science, ICT & Future Planning; and MOT Graduate School Program through the Korea Institute for the Advancement of Technology (KIAT) funded by the Ministry of Trade, Industry & Energy.

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Correspondence to Dong-hyun Oh.

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Ahn, J., Oh, Dh. & Lee, JD. The scientific impact and partner selection in collaborative research at Korean universities. Scientometrics 100, 173–188 (2014). https://doi.org/10.1007/s11192-013-1201-7

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