Skip to main content
Log in

The determinants of research collaboration modes: exploring the effects of research and researcher characteristics on co-authorship

  • Published:
Scientometrics Aims and scope Submit manuscript

Abstract

Given the high priority accorded to research collaboration on the assumption that it yields higher productivity and impact rates than do non-collaborative results, research collaboration modes are assessed for their benefits and costs before being executed. Researchers are accountable for selecting their collaboration modes, a decision made through strategic decision making influenced by their environments and the trade-offs among alternatives. In this context, by using bibliographic information and related internal data from the Korea Institute of Machinery and Materials (KIMM, a representative Korean government institute of mechanical research), this paper examines the suggested yet unproven determinants of research collaboration modes that the SCI data set cannot reveal through a Multinomial Probit Model. The results indicate that informal communication, cultural proximity, academic excellence, external fund inspiration, and technology development levels play significant roles in the determination of specific collaboration modes, such as sole research, internal collaboration, domestic collaboration, and international collaboration. This paper refines collaboration mode studies by describing the actual collaboration phenomenon as it occurs in research institutes and the motivations prompting research collaboration, allowing research mangers to encourage researchers to collaborate in an appropriate decision-making context.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1

Similar content being viewed by others

Notes

  1. Although the significance of the intercept on international collaboration does not satisfy at the given statistical significant levels (p < 0.1), it can be broadly interpreted to indicate that researchers tend to prefer international collaboration over sole research as long as the sign of the coefficient in the intercept is positive.

  2. Public institutes generally have similar management systems due to government control. Thus, our result could reflect a generic trait of public institutes, different from universities in terms of the relationship between the assessment of research achievement and collaboration tendency.

  3. None of the literature on the determinants of co-authorship uses bibliographic data drawn from the sciences and social sciences (Frame and Carpenter 1979; Mcdowell and Melvin 1983; Luukkonen et al. 1992; Piette and Ross 1992; Traore and Landry 1997; Laband and Tollison 2000; Wagner 2005; Acedo et al. 2006; Vafeas 2010). This is probably due to the distinct nature of each discipline and the difficulty of data mining. Even if a data-set were obtained, it would be very costly and difficult to connect the characteristics of the researchers and their research to the bibliographic data.

References

  • 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.

    Article  Google Scholar 

  • Becker, G. (1962). Investment in human capital: A theoretical analysis. Journal of Political Economics, 70, 9–49.

    Article  Google Scholar 

  • Bickel, W. E., & Hattrup, R. A. (1995). Teachers and researchers in collaboration: Reflections on the process. American Educational Research Journal, 32, 35–62.

    Google Scholar 

  • Bozeman, B. (2004). Scientists’ collaboration strategies: Implications for scientific and technical human capital. Research Policy, 33, 599–616. doi:10.1016/j.respol.2004.01.008.

    Article  Google Scholar 

  • Brousseau, E. (1993). L’economie des contrats. Paris: Presses Universitaires de France.

    Google Scholar 

  • Crane, D. (1972). Invisible colleges. Chicago, IL: University of Chicago Press.

    Google Scholar 

  • Cronin, B. (1996). Rates of return of citation. Journal of Documentation, 52(2), 188–197.

    Google Scholar 

  • Easterby-Smith, M., & Malina, D. (1999). Cross-cultural collaborative research: Toward reflexivity. Academy of Management Journal, 42, 76–86.

    Article  Google Scholar 

  • Edge, D. (1979). Quantitative measures of communication in science: A critical review. History of Science, 17, 102–134.

    Google Scholar 

  • Frame, J. D., & Carpenter, M. P. (1979). International research collaboration. Social Studies of Science, 9, 481–497.

    Article  Google Scholar 

  • Geweke, J., Keane, M., & Runkle, D. (1994). Alternative computational approaches to statistical interference in the multinomial probit model. Review of Economics and Statistics, 76, 609–632.

    Article  Google Scholar 

  • Goffman, W., & Warren, K. S. (1980). Scientific information systems and the principle of selectivity. New York, NY: Praeger.

    Google Scholar 

  • Hagstrom, W. O. (1965). The scientific community. New York, NY: Basic Books.

    Google Scholar 

  • Hamermesh, D. S., Johnson, G. E., & Weisbrod, B. A. (1982). Scholarship, citation and salaries: Economic reward in economics. Southern Economic Journal, 49, 472–481.

    Article  Google Scholar 

  • Hudson, J. (1996). Trends in multi-authored papers in economics. Journal of Economics Perspectives, 10, 153–158.

    Article  MathSciNet  Google Scholar 

  • Imai, K., & Dykz, D. A. (2005). MNP: R Package for fitting the multinomial probit model. Journal of Statistical Software, 14, 1–32.

    Google Scholar 

  • Jones, B. F., Wuchty, S., & Uzzi, B. (2008). Multi-university research teams: Shifting impact, geography, and stratification in science. Science, 322, 1259–1262.

    Article  Google Scholar 

  • Katz, J. S., & Martin, B. R. (1997). What is research collaboration? Research Policy, 26, 1–18.

    Article  Google Scholar 

  • Kreiner, K., & Schultz, M. (1993). Informal collaboration in R&D. The formation of networks across organizations. Organization Studies, 14, 189–209.

    Article  Google Scholar 

  • Laband, D. N., & Tollison, R. D. (2000). Intellectual collaboration. Journal of Political Economy, 108, 632–662.

    Article  Google Scholar 

  • Landry, R., Traore, N., & Godin, B. (1996). An econometric analysis of the effect of collaboration on academic research productivity. Higher Education, 32, 283–301.

    Article  Google Scholar 

  • Laudel, G. (2001). Collaboration, creativity and rewards: Why and how scientists collaborate. International Journal of Technology Management, 22, 762–781.

    Article  Google Scholar 

  • Laudel, G. (2002). What do we measure by co-authorships? Research Evaluation, 11, 3–15.

    Article  Google Scholar 

  • Lewison, G., & Cunningham, P. (1991). Bibliometric studies for the evaluation of transnational research. Scientometrics, 21, 325–342.

    Article  Google Scholar 

  • 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.

    Article  Google Scholar 

  • Luukkonen, T., Perterson, O., & Siversen, G. (1992). Understanding patterns of international scientific collaboration. Science, Technology and Human Values, 17, 101–126.

    Article  Google Scholar 

  • Martin, B. R., & Skea, J. E. F. (1992). Academic research performance indicators: An assessment of the possibilities. Brighton, UK: University of Sussex.

  • McCulloch, R. E., Polson, N. G., & Rossi, P. E. (2000). A Bayesian analysis of the multinomial probit model with fully identified parameters. Journal of Econometrics, 99, 173–193.

    Article  MATH  Google Scholar 

  • Mcdowell, J. M., & Melvin, M. (1983). The determinants of co-authorship: An analysis of the economics literature. The Review of Economics and Statistics, 65, 155–160.

    Article  Google Scholar 

  • Melin, G., & Persson, O. (1996). Studying research collaboration using co-authorships. Scientometrics, 36, 363–377.

    Article  Google Scholar 

  • Moore, M., & Griffin, B. (2006). Identification of factors that influence authorship name placement and decisions to collaborate in peer-reviewed education-related publications. Studies in Educational Evaluation, 32, 125–135.

    Article  Google Scholar 

  • 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.

    Google Scholar 

  • Nathan, S., Hermanson, D., & Hermanson, R. (1998). Co-authoring in refereed journals: Views of accounting faculty and department chairs. Issues in Accounting Education, 12, 79–92.

    Google Scholar 

  • Newman, M. E. J. (2001). Scientific collaboration networks. Physical Review E, 64. doi:10.1103/PhysRevE.64.016131.

  • Numprasertchai, S., & Igel, B. (2005). Managing knowledge through collaboration: Multiple case studies of managing research in university laboratories in Thailand. Technovation, 25(10), 1173–1182.

    Google Scholar 

  • Nyden, P., & Wiewel, W. (1992). Collaborative research: Harnessing the tensions between researcher and practitioner. American Sociologist, 23, 43–55.

    Article  Google Scholar 

  • 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.

    Article  Google Scholar 

  • Rutledge, R., & Karim, K. (2009). Determinants of coauthorship for the most productive authors of accounting literature. The Journal of Education for Business, 84(3), 130–134.

    Google Scholar 

  • Sauer, R. D. (1988). Estimates of the return to quality and coauthorship in economic academy. Journal of Political Economy, 96, 855–866.

    Article  Google Scholar 

  • Simonin, B. L. (1997). The importance of collaborative know-how: An empirical test of the learning organization. Academy of Management Journal, 40, 1150–1174.

    Article  Google Scholar 

  • Solla Price, D., & Beaver, D. (1966). Collaboration in an invisible college. American Psychologist, 21, 1011–1018.

    Article  Google Scholar 

  • Train, K., & Sonnier, G. (2005). Mixed logit with bounded distribution of partworths. In R. Scarpa & A. Alberini (Eds.), Applications of simulation methods in environmental and resource economics (pp. 117–134). Dordrecht: Springer.

    Chapter  Google Scholar 

  • Traore, N., & Landry, R. (1997). On the determinants of scientists’ collaboration. Science Communication, 19, 124–140.

    Article  Google Scholar 

  • Vafeas, N. (2010). Determinants of single authorship. EuroMed Journal of Business, 5, 332–344.

    Article  Google Scholar 

  • van Raan, A. F. J. (1998). The influence of international collaboration on the impact of research result. Scientometrics, 42, 423–428.

    Article  Google Scholar 

  • van Rijnsoever, F. J., & Hessels, L. K. (2010). Factors associated with disciplinary and interdisciplinary research collaboration. Research Policy, 40(3), 463–472.

    Article  Google Scholar 

  • Wagner, C. S. (2005). Six case studies of international collaboration in science. Scientometrics, 62, 3–26.

    Article  Google Scholar 

  • 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.

    Google Scholar 

  • Wagner, C. S., & Leydesdorff, L. (2005). Network structure, self-organization, and the growth of international collaboration in science. Research Policy, 34, 1608–1618.

    Article  Google Scholar 

  • Wagner, C. S., Brahmakulam, I., Jackson, B., Wong, A., & Yoda, T. (2001). Science and technology collaboration: building capacity in developing countries? MR-1357.0-WB. Santa Monica, CA: RAND.

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Jae Young Choi.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Jeong, S., Choi, J.Y. & Kim, J. The determinants of research collaboration modes: exploring the effects of research and researcher characteristics on co-authorship. Scientometrics 89, 967–983 (2011). https://doi.org/10.1007/s11192-011-0474-y

Download citation

  • Received:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11192-011-0474-y

Keywords

Mathematics Subject Classification

JEL Classification

Navigation