Author:
Authors:
and
Seongkyoon Jeong
Seongkyoon Jeong
Department of Research and Development Policy, Korea Institute of Machinery and Materials (KIMM), 156, Gajungbukno, Yuseong-Gu, Daejeon 305-343, Korea
Search for other papers by Seongkyoon Jeong in
Current site
Google Scholar
PubMed
Search for other papers by Seongkyoon Jeong in
Current site
Google Scholar
PubMed
Jae Young Choi
Jae Young Choi
Center for Growth Engine Industries, Korea Institute for Industrial Economics and Trade (KIET) 66, Hoegiro, Dongdaemun-gu, Seoul, Korea
Search for other papers by Jae Young Choi in
Current site
Google Scholar
PubMed
Search for other papers by Jae Young Choi in
Current site
Google Scholar
PubMed
Abstract
This paper suggests an empirical framework to classify research collaboration activities with developed indicators that carry on a previous theoretical framework (Wagner [Science and Technology Policy for Development, 2006]; Wagner et al. [Linking effectively: Learning lessons from successful collaboration in science and technology. DB-345-OSTP, 2002]) by employing the Gaussian mixture model, an advanced probabilistic clustering analysis. By further exploring the method upon a profound evidence-based reflection of actual phenomena, this paper also proposes an exploratory analysis to manage and evaluate research projects upon their differentiated classification in a preceding perspective of research collaboration and R&D management. In addition, the results show that international collaboration tends to be associated with more evenly committed collaboration, and that collaboration featuring a higher degree of funding or dispersed commitments generally results in larger outcomes than research clustered on the opposite side of the framework.
ProCite
RefWorks
Reference Manager
BibTeX
Zotero
EndNote
-
Abramo, G, D’Angelo, CA, Solazzi, M 2011 The relationship between scientists’ research performance and the degree of internationalization of their research. Scientometrics 86 3 629–643 .
-
Acedo, FJ, Barroso, C, Casanueva, C, Galán, JL 2006 Co-authorship in management and organizational studies: An empirical and network analysis. Journal of Management Studies 43 5 957–983 .
-
Bouman, CA, Shapiro, M, Cook, GW, Atkins, CB, Cheng, H, Jennifer, G, Borman, S 2005 Cluster: An unsupervised algorithm for modeling gaussian mixtures School of Electrical Engineering Purdue University West Lafayette.
-
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 .
-
Cheng, J, Yang, J, Zhou, Y 2005 A novel adaptive Gaussian mixture model for background subtraction. Lecture Notes in Computer Science 3522:587–593 .
-
Cohen, WM, Nelson, RR, Walsh, JP 2002 Links and impacts: The influence of public research on industrial R&D. Management Science 48 1 1–23 .
-
Crane, D 1972 Invisible colleges University of Chicago Press Chicago.
-
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.
-
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.
-
Edge, D 1979 Quantitative measures of communication in science: A critical review. History of Science 17:102–134.
-
Frame, JD 1987 Managing projects in organizations. How to make best use of time, techniques, and people Jossey-Bass San Francisco.
-
Goffman, W, Warren, KS 1980 Scientific information systems and the principle of selectivity Praeger New York.
-
Hagstrom, WO 1965 The scientific community Basic Books New York.
-
Han, DS, Jang, DH, Han, SH, Yang, JM 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.
-
Hansen, MH, Yu, B 2001 Model selection and the principle of minimum description length. Journal of American Statistical Association 96 454 746–774 .
-
Hinings, CR, Greenwood, R 1996 Working together PJ Frost SM Taylor eds. Rhythms of academic life: Personal accounts of careers in Academia Sage Thousand Oaks 225–237.
-
Hoegl, M, Gemuenden, HG 2001 Teamwork quality and the success of innovative projects: A theoretical concept and empirical evidence. Organization Science 12 4 435–449 .
-
Kashyap, RL 1980 Inconsistency of the AIC rule for estimating the order of autoregressive models. IEEE Transactions on Automatic Control 25 5 996–998 .
-
Katz, JS, Martin, BR 1997 What is research collaboration?. Research Policy 26:1–18 .
-
Laband, DN, Tollison, RD 2000 Intellectual collaboration. Journal of Political Economy 108:632–662 .
-
Laudel, G 2002 What do we measure by co-authorships?. Research Evaluation 11:3–15 .
-
Liao, CH 2011 How to improve research quality? Examining the impacts of collaboration intensity and member diversity in collaboration networks. Scientometrics 86 3 747–761 .
-
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 .
-
Martin, B, Salter, A 1996 The relationship between publicly funded basic research and economic performance. Report of the science and policy research Unit University of Sussex East Sussex.
-
Melin, G, Persson, O 1996 Studying research collaboration using co-authorships. Scientometrics 36:363–377 .
-
Narin, F, Whitlow, ES 1990 Measurement of scientific cooperation and coauthorship in CEC-related areas of science (report EUR 12900) Office for Official Publications of the European Communities Luxembourg.
-
Newman, M. E. J. (2001). Scientific collaboration networks. Physical Review E, 64. doi: .
-
Payne, J 1995 Management of multiple simultaneous projects: A state-of-the-art review. International Journal of Project Management 13 3 163–168 .
-
Pfeffer, J, Salancik, GR 1978 The design and management of externally controlled organization Harper and Row New York.
-
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.
-
Rissanen, J 1983 A universal prior for integers and estimation by minimum description length. Annals of Statistics 11 2 417–431 .
-
Schwarz, G 1978 Estimating the dimension of a model. Annals of Statistics 6 2 461–464 .
-
Smith, D, Katz, JS 2000 Collaborative approaches to research, HEFCE fund review of research policy and funding University of Sussex East Sussex.
-
Solla Price, D, Beaver, D 1966 Collaboration in an invisible college. American Psychologist 21:1011–1018 .
-
Thomson, JD 1967 Organizations in Action McGraw-Hill NY.
-
Traore, N., & Landry, R. (1997). On the determinants of scientists’ collaboration. Science Communication, 19, 124–140.
-
Um, I. (2011). The determinants of R&D budget. Doctoral dissertation, Kookmin University, Seoul.
-
Vafeas, N. (2010). Determinants of single authorship. EuroMed Journal of Business, 5, 332–344.
-
AFJ van Raan 1998 The influence of international collaboration on the impact of research result. Scientometrics 42:423–428 .
-
Wagner, CS 2005 Six case studies of international collaboration in science. Scintrometrics 62:3–26 .
-
Wagner, CS 2006 International collaboration in science and technology: Promises and pitfalls B Louk E Rutger eds. Science and technology policy for development, dialogues at the interface Anthem Press London 165–176.
-
Wagner, CS, Leydesdorff, L 2005 Network structure, self-organization, and the growth of international collaboration in science. Research Policy 34:1608–1618 .
-
Wagner, CS, Staheli, L, Silberglitt, R, Wong, A, Kadtke, J 2002 Linking effectively: Learning lessons from successful collaboration in science and technology. DB-345-OSTP RAND Santa Monica.
-
Wagner, C, Yezril, A, Hassell, S 2000 International cooperation in research and development: An update to an inventory of US government spending, MR-1248 RAND Santa Monica.
-
Woolley, AW, Chabris, CF, Pentland, A, Hashmi, N, Malone, TW 2010 Evidence for a collective intelligence factor in the performance of human groups. Science 330 6004 686–688 .
To see the editorial board, please visit the website of Springer Nature.
Manuscript submission: http://www.editorialmanager.com/scim/
For subscription options, please visit the website of Springer Nature.
| Scientometrics | |
|---|---|
| Language | English |
| Size | B5 |
| Year of Foundation |
1978 |
| Volumes per Year |
1 |
| Issues per Year |
12 |
| Founder | Akadémiai Kiadó |
| Founder's Address |
H-1117 Budapest, Hungary 1516 Budapest, PO Box 245. |
| Publisher | Akadémiai Kiadó Springer Nature Switzerland AG |
| Publisher's Address |
H-1117 Budapest, Hungary 1516 Budapest, PO Box 245. CH-6330 Cham, Switzerland Gewerbestrasse 11. |
| Responsible Publisher |
Chief Executive Officer, Akadémiai Kiadó |
| ISSN | 0138-9130 (Print) |
| ISSN | 1588-2861 (Online) |
Monthly Content Usage
| Abstract Views | Full Text Views | PDF Downloads | |
|---|---|---|---|
| Dec 2024 | 35 | 0 | 0 |
| Jan 2025 | 70 | 0 | 0 |
| Feb 2025 | 87 | 0 | 0 |
| Mar 2025 | 84 | 0 | 0 |
| Apr 2025 | 26 | 0 | 0 |
| May 2025 | 5 | 0 | 0 |
| Jun 2025 | 0 | 0 | 0 |
Author:
Author:
Author:
Copyright Akadémiai Kiadó AKJournals is the trademark of Akadémiai Kiadó's journal publishing business branch.
Powered by PubFactory