DOI QR코드

DOI QR Code

Collaborative Research Network and Scientific Productivity: The Case of Korean Statisticians and Computer Scientists

  • Kwon, Ki-Seok (Department of Public Policy, Hanbat National University) ;
  • Kim, Jin-Guk (Department of Business Consulting, Pai Chai University)
  • Received : 2017.03.29
  • Accepted : 2017.04.25
  • Published : 2017.04.28

Abstract

This paper focuses on the relationship between the characteristics of network and the productivity of scientists, which is rarely examined in previous studies. Utilizing a unique dataset from the Korean Citation Index (KCI), we examine the overall characteristics of the research network (e.g. distribution of nodes, density and mean distance), and analyze whether the network centrality is related to the scientific productivity. According to the results, firstly we have found that the collaborative research network of the Korean academics in the field of statistics and computer science is a scale-free network. Secondly, these research networks show a disciplinary difference. The network of statisticians is denser than that of computer scientists. In addition, computer scientists are located in a fragmented network compared to statisticians. Thirdly, with regard to the relationship between the researchers' network position and scientific productivity, a significant relation and their disciplinary difference have been observed. In particular, the degree centrality is the strongest predictor for the scientists' productivity. Based on these findings, some policy implications are put forward.

Keywords

References

  1. Abramo, G., D'Angelo, C.A. and Pugini, F. (2007) The measurement of Italian universities' research productivity by a non-parametric-bibliometric methodology, Scientometrics, 76(2), 225-244. https://doi.org/10.1007/s11192-007-1942-2
  2. Barabasi, A.L., Jeong, H., Neda, Z., Ravasz, E., Schubert, A. and Vicsek, T. (2002) Evolution of the social network of scientific collaborations, Physica A: Statistical Mechanics and its Applications, 311(3-4), 590-614. https://doi.org/10.1016/S0378-4371(02)00736-7
  3. Bordons, M., Go'mez, I., Ferna'ndez, M.T., Zulueta, M.A. and Me'ndez, A. (1996) Local, domestic and international scientific collaboration in biomedical research, Scientometrics, 37(2), 279-295. https://doi.org/10.1007/BF02093625
  4. Kim, Y.H., Yoon, J.R., Cho, H. and Kim, Y.J. (2007) Structure of collaboration network among Korean scientists -'small world' and position effect (in Korean), Korean Journal of Sociology, 41(1), 68-103.
  5. Smeby, J. and Try, S. (2005) Departmental contexts and faculty research activity in Norway, Research in Higher Education, 46(6), 593-619. https://doi.org/10.1007/s11162-004-4136-2
  6. Stephan, P.E. (1996) The economics of science, Journal of Economic Literature, 36, 1199-1235.
  7. Stephan, P.E. and Levin S.G. (1992) Striking the Mother Lode: The Importance of Age, Place, and Time, New York and Oxford: Oxford University Press.
  8. Van Raan, A.F.J. (1998) The influence of international collaboration of the impact of the research results, Scientometrics, 42(3), 423-428. https://doi.org/10.1007/BF02458380

Cited by

  1. An Analysis of Higher Education Policy: The Case of Government-Supported University Programs in South Korea vol.7, pp.2, 2018, https://doi.org/10.7545/ajip.2018.7.2.364