The taxonomy of research collaboration in science and technology: Evidence from mechanical research through probabilistic clustering analysis

Scientometrics

Volumn 91, Issue 3, 2012, Pages 719-735

  Jeong, Seongkyoon ^a   Choi, Jae Young ^b  

^a Korea Institute of Machine and Materials   (South Korea)

^b Korea Institute for Industrial Economics and Trade   (South Korea)

Author keywords

Clustering; Gaussian mixture; Research and development strategy; Research collaboration

Indexed keywords

EID: 84862803010     PISSN: 01389130     EISSN: None     Source Type: Journal    
DOI: 10.1007/s11192-012-0686-9     Document Type: Article

References (45)

1. Abramo, G., D'Angelo, C. A., & Solazzi, M. (2011). The relationship between scientists' research performance and the degree of internationalization of their research. Scientometrics, 86(3), 629-643.
2. Acedo, F. J., Barroso, C., Casanueva, C., & Galán, J. L. (2006). Co-authorship in management and organizational studies: An empirical and network analysis. Journal of Management Studies, 43(5), 957-983.
3. Bouman, C. A., Shapiro, M., Cook, G. W., Atkins, C. B., Cheng, H., Jennifer, G., et al. (2005). Cluster: An unsupervised algorithm for modeling gaussian mixtures. West Lafayette: School of Electrical Engineering Purdue University.
4. Breschi, S., & Malerba, F. (2011). Assessing the scientific and technological outcome of EU framework programmes: Evidence from the FP6 projects in the ICT field. Scientometrics, 88(1), 239-257.
5. Cheng, J., Yang, J., & Zhou, Y. (2005). A novel adaptive Gaussian mixture model for background subtraction. Lecture Notes in Computer Science, 3522, 587-593.
6. Cohen, W. M., Nelson, R. R., & Walsh, J. P. (2002). Links and impacts: The influence of public research on industrial R& D. Management Science, 48(1), 1-23.
7. Crane, D. (1972). Invisible colleges. Chicago: University of Chicago Press.
8. Crowston, K. (1994). A taxonomy of organisational dependencies and coordination mechanisms. MIT Center for Coordination Science Working Paper. Massachusetts Institute of Technology. Retrieved from http://ccs. mit. edu/ccsmainhtml). Accessed 1 June 2011.
9. Dempster, A., Laird, N., & Rubin, D. (1977). Maximum likelihood from incomplete data via the EM algorithm. Journal of Royal Statistical Society Series B, 39(1), 1-38.
10. Edge, D. (1979). Quantitative measures of communication in science: A critical review. History of Science, 17, 102-134.
11. Frame, J. D. (1987). Managing projects in organizations. How to make best use of time, techniques, and people. San Francisco: Jossey-Bass.
12. Goffman, W., & Warren, K. S. (1980). Scientific information systems and the principle of selectivity. New York: Praeger.
13. Hagstrom, W. O. (1965). The scientific community. New York: Basic Books.
14. Han, D. S., Jang, D. H., Han, S. H., & Yang, J. M. (2008). An empirical study on the impacts of public funding on the research performance of academic faculties. Korean Public Administration Review, 42(4), 265-290.
15. Hansen, M. H., & Yu, B. (2001). Model selection and the principle of minimum description length. Journal of American Statistical Association, 96(454), 746-774.
16. Hinings, C. R., & Greenwood, R. (1996). Working together. In P. J. Frost & S. M. Taylor (Eds.), Rhythms of academic life: Personal accounts of careers in Academia (pp. 225-237). Thousand Oaks: Sage.
17. Hoegl, M., & Gemuenden, H. G. (2001). Teamwork quality and the success of innovative projects: A theoretical concept and empirical evidence. Organization Science, 12(4), 435-449.
18. Kashyap, R. L. (1980). Inconsistency of the AIC rule for estimating the order of autoregressive models. IEEE Transactions on Automatic Control, 25(5), 996-998.
19. Katz, J. S., & Martin, B. R. (1997). What is research collaboration? Research Policy, 26, 1-18.
20. Laband, D. N., & Tollison, R. D. (2000). Intellectual collaboration. Journal of Political Economy, 108, 632-662.
21. Laudel, G. (2002). What do we measure by co-authorships? Research Evaluation, 11, 3-15.
22. Liao, C. H. (2011). How to improve research quality? Examining the impacts of collaboration intensity and member diversity in collaboration networks. Scientometrics, 86(3), 747-761.
23. Lundberg, J., Tomson, G., Lundkvist, I., Skar, J., & Brommels, M. (2006). Collaboration uncovered: Exploring the adequacy of measuring university-industry collaboration through co-authorship and funding. Scientometrics, 69, 575-589.
24. Martin, B., & Salter, A. (1996). The relationship between publicly funded basic research and economic performance. Report of the science and policy research Unit. East Sussex: University of Sussex.
25. Melin, G., & Persson, O. (1996). Studying research collaboration using co-authorships. Scientometrics, 36, 363-377.
26. Narin, F., & Whitlow, E. S. (1990). Measurement of scientific cooperation and coauthorship in CEC-related areas of science (report EUR 12900). Luxembourg: Office for Official Publications of the European Communities.
27. Newman, M. E. J. (2001). Scientific collaboration networks. Physical Review E, 64. doi: 10. 1103/PhysRevE. 64. 016131.
28. Payne, J. (1995). Management of multiple simultaneous projects: A state-of-the-art review. International Journal of Project Management, 13(3), 163-168.
29. Pfeffer, J., & Salancik, G. R. (1978). The design and management of externally controlled organization. New York: Harper and Row.
30. Piette, M. J., & Ross, K. L. (1992). An analysis of the determinants of co-authorship in economics. The Journal of Economic Education, 23, 277-283.
31. Rissanen, J. (1983). A universal prior for integers and estimation by minimum description length. Annals of Statistics, 11(2), 417-431.
32. Schwarz, G. (1978). Estimating the dimension of a model. Annals of Statistics, 6(2), 461-464.
33. Smith, D., & Katz, J. S. (2000). Collaborative approaches to research, HEFCE fund review of research policy and funding. East Sussex: University of Sussex.
34. Solla Price, D., & Beaver, D. (1966). Collaboration in an invisible college. American Psychologist, 21, 1011-1018.
35. Thomson, J. D. (1967). Organizations in Action. NY: McGraw-Hill.
36. Traore, N., & Landry, R. (1997). On the determinants of scientists' collaboration. Science Communication, 19, 124-140.
37. Um, I. (2011). The determinants of R & D budget. Doctoral dissertation, Kookmin University, Seoul.
38. Vafeas, N. (2010). Determinants of single authorship. EuroMed Journal of Business, 5, 332-344.
39. van Raan, A. F. J. (1998). The influence of international collaboration on the impact of research result. Scientometrics, 42, 423-428.
40. Wagner, C. S. (2005). Six case studies of international collaboration in science. Scintrometrics, 62, 3-26.
41. Wagner, C. S. (2006). International collaboration in science and technology: Promises and pitfalls. In B. Louk & E. Rutger (Eds.), Science and technology policy for development, dialogues at the interface (pp. 165-176). London: Anthem Press.
42. Wagner, C. S., & Leydesdorff, L. (2005). Network structure, self-organization, and the growth of international collaboration in science. Research Policy, 34, 1608-1618.
43. Wagner, C. S., Staheli, L., Silberglitt, R., Wong, A., & Kadtke, J. (2002). Linking effectively: Learning lessons from successful collaboration in science and technology. DB-345-OSTP. Santa Monica: RAND.
44. Wagner, C., Yezril, A., & Hassell, S. (2000). International cooperation in research and development: An update to an inventory of US government spending, MR-1248. Santa Monica: RAND.
45. Woolley, A. W., Chabris, C. F., Pentland, A., Hashmi, N., & Malone, T. W. (2010). Evidence for a collective intelligence factor in the performance of human groups. Science, 330(6004), 686-688. doi: 10. 1126/science. 1193147.