Skip to main content
SpringerLink
Log in

Collaboration in pharmaceutical research: exploration of country-level determinants

  • Published:
Scientometrics Aims and scope Submit manuscript

Abstract

In this paper we focus on proximity as one of the main determinants of international collaboration in pharmaceutical research. We use various count data specifications of the gravity model to estimate the intensity of collaboration between pairs of countries as explained by the geographical, cognitive, institutional, social, and cultural dimensions of proximity. Our results suggest that geographical distance has a significant negative relation to the collaboration intensity between countries. The amount of previous collaborations, as a proxy for social proximity, is positively related to the number of cross-country collaborations. We do not find robust significant associations between cognitive proximity or institutional proximity with the intensity of international research collaboration. Our findings for cultural proximity do not allow of unambiguous conclusions concerning their influence on the collaboration intensity between countries.

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

Access this article

Log in via an institution

Subscribe and save

Springer+ Basic
$34.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

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

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1

Similar content being viewed by others

Notes

  1. The trade literature suggests to add origin and destination fixed effects to the analysis (e.g., Helpman et al. 2008). However, this approach is not applicable in the case of scientific collaborations since these represent undirected interactions whereas trade flows are directed interactions. Moreover, trade cost may be better observable than the cost of collaboration which are not available in our dataset.

  2. http://www.infinata5.com/biopharm/.

  3. Table 3 provides an overview of the therapeutic areas included in the dataset.

  4. The subcategories are described in detail at http://scientific.thomsonreuters.com/mjl/.

  5. Appendix 1 provides a description of the variables.

  6. See Figs. 2 and 3 in the Appendix 2 for a more detailed illustration.

  7. Results not presented in this paper are available upon request.

  8. Another interpretation may stress that the former colonizers may want to support scientific and economic development in their former colonies. Therefore, governments may encourage scientists to collaborate with researchers based in former colonies of the respective country.

  9. A list of science and technology agreements signed by the European Union can be obtained from the European Commission’s web site: http://ec.europa.eu/research/iscp/index.cfm?lg=en&pg=countries.

References

  • Acosta, M., Coronado, D., Ferrádiz, E., & León, M. (2011). Factors affecting inter-regional academic scientific collaboration within Europe: The role of economic distance. Scientometrics, 87(1), 63–74.

    Article  Google Scholar 

  • Adams, J.D., Black, G. C., Clemmons, J. R., & Stephan, P. E. (2005). Scientific teams and institutional collaborations: Evidence from U.S. Universities, 1981–1999. Research Policy, 34(3), 259–285.

    Article  Google Scholar 

  • Agrawal, A., Cockburn, I., & McHale, J. (2006). Gone but not forgotten: Knowledge flows, labor mobility, and enduring social relationships. Journal of Economic Geography, 6(5), 571–591.

    Article  Google Scholar 

  • Asheim, B., Coenen, L., & Vang, J. (2007). Face-to-face, buzz, and knowledge bases: Sociospatial implications for learning, innovation, and innovation policy. Environment and Planning C: Government and Polic, 25(5), 655–670.

    Article  Google Scholar 

  • Audretsch, D. B., & Feldman, M. P. (1996). R&D spillovers and the geography of innovation and production. The American Economic Review, 86(3), 630–640.

    Google Scholar 

  • Autant-Bernard, C., Billand, P., Frachisse, D., & Massard, N. (2007). Social distance versus spatial distance in R&D cooperation: Empirical evidence from European collaboration choices in micro and nanotechnologies. Papers in Regional Science, 86(3), 495–519.

    Article  Google Scholar 

  • Balland, P.-A. (2012). Proximity and the evolution of collaboration networks: Evidence from research and development projects within the global navigation satellite system (GNSS) industry. Regional Studies, 46(6), 741–756. forthcoming.

    Google Scholar 

  • Bartholomew, S. (1997). National systems of biotechnology innovation: Complex interdependence in the global system. Journal of International Business Studies, 28(2), 241–266.

    Article  MathSciNet  Google Scholar 

  • Basile, R., Capello, R., & Caragliu, A. (2012). Technological interdependence and regional growth in Europe: Proximity and synergy in knowledge spillovers. Papers in Regional Science, 91(4), 697–722.

    Google Scholar 

  • Boschma, R. (2005). Proximity and innovation: A critical assessment. Regional Studies, 39(1):61–74.

    Article  Google Scholar 

  • Boschma, R., & Lambooy, J. G. (1999). Evolutionary economics and economic geography. Journal of Evolutionary Economics, 9(4), 411–429.

    Article  Google Scholar 

  • Boshoff, N. (2009). Neo-colonialism and research collaboration in Central Africa. Scientometrics, 81(2), 413–434.

    Article  Google Scholar 

  • Broekel, T., & Boschma, R. (2012). Knowledge networks in the Dutch aviation industry: The proximity paradox. Journal of Economic Geography, 12(2), 409–433.

    Article  Google Scholar 

  • Burger, M., van Oort, F., & Linders, G.-J. (2009). On the specification of the gravity model of trade: Zeros, excess zeros and zero-inflated estimation. Spatial Economic Analysis, 4(2), 167–190.

    Article  Google Scholar 

  • Cameron, A. C., & Trivedi, P. K. (1990). Regression-based tests for overdispersion in the Poisson model. Journal of Econometrics, 46(3), 347–364.

    Article  MathSciNet  Google Scholar 

  • Cantner, U., & Meder, A. (2007). Technological proximity and the choice of cooperation partner. Journal of Economic Interaction and Coordination, 2(1), 45–65.

    Article  Google Scholar 

  • Choi, S. (2012). Core-periphery, new clusters, or rising stars? International scientific collaboration among ‘advanced’ countries in the era of globalization. Scientometrics, 90(1), 25–41.

    Article  Google Scholar 

  • Coenen, L., Moodysson, J., & Asheim, B. T. (2004). Nodes, networks and proximities: On the knowledge dynamics of the Medicon Valley biotech cluster. European Planning Studies, 12(7), 1003–1018.

    Google Scholar 

  • Cohen, W. M., & Levinthal, D. A. (1990). Absorptive capacity: A new perspective on learning and innovation. Administrative Science Quarterly, 35(1), 128–152.

    Article  Google Scholar 

  • de Crombrugghe, D., Farla, K., Meisel, N., de Neubourg, C., Aoudia, J. O., & Szirmai, A. (2009). Institutional profiles database III—Presentation of the institutional profiles database 2009 (IPD 2009). Documents des Travail de la DGTPE, 2009/14.

  • de Solla Price, D. (1963). Little science, big science. New York: Columbia University Press.

    Google Scholar 

  • Dosi, G., Pavitt, K., & Soete, L. (1990). The economics of technical change and international trade. New York: Harvester Wheatsheaf.

    Google Scholar 

  • Edquist, C., & Johnson, B. (1997). Institutions and organizations in systems of innovation. in Systems of innovation: Technologies, institutions, and organizations (pp. 41–63). London: Pinter.

  • Felbermayr, G. J., & Toubal, F. (2010). Cultural proximity and trade. European Economic Review, 54(2), 279–293.

    Article  Google Scholar 

  • Flowerdew, R., & Aitkin, M. (1982). A method of fitting the gravity model based on the Poisson distribution. Journal of Regional Science, 22(2), 191–202.

    Article  Google Scholar 

  • Frenken, K., Hoekman, J., Kok, S., Ponds, R., van Oort, F., & van Vliet, J. (2009). Death of distance in science? A gravity approach to research collaboration. In A. Pyka, & A. Scharnhorst (Eds.), Innovation networks (pp. 43–57). Berlin: Springer.

    Chapter  Google Scholar 

  • Furman, J. L., Porter, M. E., & Stern, S. (2002). The determinants of national innovative capacity. Research Policy, 31(6), 899–933.

    Article  Google Scholar 

  • Gertler, M. S. (1995). “Being there”: Proximity, organization, and culture in the development and adoption of advanced manufacturing technologies. Economic Geography, 71(1), 1–26.

    Article  Google Scholar 

  • Granovetter, M. (1985). Economic action and social structure: The problem of embeddedness. The American Journal of Sociology, 91(3), 481–510.

    Article  Google Scholar 

  • Greene, W. H. (1994). Accounting for excess zeros and sample selection in Poisson and negative binomial regression models. NYU Working Paper, No. EC-94-10.

  • Hagedoorn, J. (2002). Inter-firm R&D partnerships: An overview of major trends and patterns since 1960. Research Policy, 31(4), 477–492.

    Article  Google Scholar 

  • Hamilton, K. S. (2003). Subfield and level classification of journals. CHI Research Inc., CHI No. 2012-R.

  • Helpman, E., Melitz, M., & Rubinstein, Y. (2008). Estimating trade flows: Trading partners and trading volumes. The Quarterly Journal of Economics, 123(2), 441–487.

    Article  MATH  Google Scholar 

  • Hoekman, J., Frenken, K., & Tijssen, R. J. (2010). Research collaboration at a distance: Changing spatial patterns of scientific collaboration within Europe. Research Policy, 39(5), 662–673.

    Article  Google Scholar 

  • Hoekman, J., Frenken, K., & van Oort, F. (2009). The geography of collaborative knowledge production in Europe. The Annals of Regional Science, 43(3), 721–738.

    Article  Google Scholar 

  • Hoekman, J., Scherngell, T., Frenken, K., & Tijssen, R. (2013). Acquisition of European research funds and its effect on international scientific collaboration. Journal of Economic Geography, 13(1), 23–52.

    Article  Google Scholar 

  • Howells, J. R. L. (2002). Tacit knowledge, innovation and economic geography. Urban Studies, 39(5-6), 871–884.

    Article  Google Scholar 

  • Isard, W. (1954). Location theory and trade theory: Short-run analysis. The Quarterly Journal of Economics, 68(2), 305–320.

    Article  Google Scholar 

  • Jaffe, A. B. (1986). Technological opportunity and spillovers of R &D: Evidence from firms’ patents, profits, and market value. The American Economic Review, 76(5), 984–1001.

    Google Scholar 

  • Jaffe, A. B., Trajtenberg, M., & Henderson, R. (1993). Geographic localization of knowledge spillovers as evidenced by patent citations. The Quarterly Journal of Economics, 108(3), 577–598.

    Article  Google Scholar 

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

    Article  Google Scholar 

  • Kirat, T., & Lung, Y. (1999). Innovation and proximity: Territories as loci of collective learning processes. European Urban and Regional Studies, 6(1), 27–38.

    Article  Google Scholar 

  • Laudel, G. (2002). What do we measure by co-authorships? Research Evaluation, 11(1), 3–15.

    Article  Google Scholar 

  • Lundberg, J., Tomson, G., Lundkvist, I., Skar, J., & Brommels, M. (2006). CCollaboration uncovered: Exploring the adequacy of measuring university–industry collaboration through co-authorship and funding. Scientometrics, 69(3), 575–589.

    Article  Google Scholar 

  • Lundvall, B. (1988). Innovation as an interactive process: From user–producer interaction to the national system of innovation. In: G. Dosi, C. Freeman, R. Nelson, G. Silverberg, & L. Soete (Eds.), Technical change and economic theory (pp. 349–369). London: Pinter.

    Google Scholar 

  • Lundvall, B.-A. (1992). National systems of innovation: Towards a theory of innovation and interactive learning. London: Pinter.

    Google Scholar 

  • Luukkonen, T., Persson, O., & Sivertsen, G. (1992). Understanding patterns of international scientific collaboration. Science, Technology & Human Values, 17(1), 101–126.

    Article  Google Scholar 

  • Mattsson, P., Laget, P., Nilsson, A., & Sundberg, C.-J. (2008). Intra-EU vs. extra-EU scientific co-publication patterns in EU. Scientometrics, 75(3), 555–574.

    Article  Google Scholar 

  • Mayer, T., & Zignago, S. (2006). Notes on CEPII’s distances measures. CEPII (Centre d’Études Prospectives et d’Information Internationales), Paris.

  • Melitz, J. (2008). Language and foreign trade. European Economic Review, 52(4), 667–699.

    Article  Google Scholar 

  • Miquel, J., & Okubo, Y. (1994). Structure of international collaboration in science, part II: Comparisons of profiles in countries using a link indicator. Scientometrics, 29(2), 271–297. doi:10.1007/BF02017977.

    Article  Google Scholar 

  • Nagpaul, P. (2003). Exploring a pseudo-regression model of transnational cooperation in science. Scientometrics, 56(3), 403–416.

    Article  Google Scholar 

  • Narin, F., Stevens, K., & Whitlow, E. (1991). Scientific co-operation in Europe and the citation of multinationally authored papers. Scientometrics, 21(3), 13–323.

    Article  Google Scholar 

  • Nooteboom, B. (2000). Learning and innovation in organizations and economies. Oxford: Oxford University Press.

    Google Scholar 

  • Peri, G. (2005). Determinants of knowledge flows and their effect on innovation. Review of Economics and Statistics, 87(2), 308–322.

    Article  Google Scholar 

  • Ponds, R., van Oort, F., & Frenken, K. (2007). The geographical and institutional proximity of research collaboration. Papers in Regional Science, 86(3), 423–443.

    Article  Google Scholar 

  • Santos Silva, J., & Tenreyro, S. (2006). The log of gravity. The Review of Economics and Statistics, 88(4), 641–658.

    Article  Google Scholar 

  • Scherngell, T., & Barber, M. J. (2009). Spatial interaction modelling of cross-region R&D collaborations: Empirical evidence from the 5th EU Framework Programme. Papers in Regional Science, 88(3), 531–546.

    Article  Google Scholar 

  • Scherngell, T., & Barber, M. J. (2011). Distinct spatial characteristics of industrial and public research collaborations: Evidence from the fifth EU Framework Programme. The Annals of Regional Science, 46(2), 247–266.

    Article  Google Scholar 

  • Scherngell, T., & Hu, Y. (2011). Collaborative knowledge production in China: Regional evidence from a gravity model approach. Regional Studies, 45(6), 755–772.

    Article  Google Scholar 

  • Schubert, A., & Glänzel, W. (2006). Cross-national preference in co-authorship, references and citations. Scientometrics, 69(2), 409–428.

    Article  Google Scholar 

  • Shan, W., & Hamilton, W. (1991). Country-specific advantage and international cooperation. Strategic Management Journal, 12(6), 419–432.

    Article  Google Scholar 

  • Tinbergen, J. (1962). Shaping the world economy: Suggestions for an international economic policy. New York: The Twentieth Century Fund.

    Google Scholar 

  • Torre, A., & Gilly, J.-P. (2000). On the analytical dimension of proximity dynamics. Regional Studies, 34(2), 169–180.

    Article  Google Scholar 

  • Torre, A., & Rallet, A. (2005). Proximity and localization. Regional Studies, 39(1), 47–59.

    Article  Google Scholar 

  • Vuong, Q. H. (1989). Likelihood ratio tests for model selection and non-nested hypotheses. Econometrica, 57(2), 307–333.

    Article  MATH  MathSciNet  Google Scholar 

  • Wagner, C. S., & Leydesdorff, L. (2005). Mapping the network of global science: Comparing international co-authorships from 1990 to 2000. International Journal of Technology and Globalisation, 1(2), 185–208.

    Article  Google Scholar 

  • Wuchty, S., Jones, B. F., & Uzzi, B. (2007). The increasing dominance of teams in production of knowledge. Science, 316(5827), 1036–1039.

    Article  Google Scholar 

  • Zeller, C. (2004). North Atlantic innovative relations of Swiss pharmaceuticals and the proximities with regional biotech arenas. Economic Geography, 80(1), 83–111.

    Article  Google Scholar 

  • Zitt, M., Bassecoulard, E., & Okubo, Y. (2000). Shadows of the past in international cooperation: Collaboration profiles of the top five producers of science. Scientometrics, 47, 627–657.

    Article  Google Scholar 

Download references

Acknowledgements

This research was partly done while the authors were members of the Graduate College “The Economics of Innovative Change” at the Friedrich Schiller University Jena. We thank the German Science Foundation (DFG) and the DIME network for financial support. We are grateful to Uwe Cantner, the participants of the Jena Economic Research Workshop in February 2011, especially to Ljubica Nedelkoska, Fang Wang and Sebastian Wilfling, the participants of the DRUID-DIME Academy Winter Conference 2011, particularly Lars Alkærsing and Tim Pohlmann, and the participants of the DIME Final Conference 2011 and to an anonymous referee for useful comments, expressed interest, and concerns. We thank Bart Leten for helping with the CHI classification. The usual caveats apply.

Author information

Authors and Affiliations

  1. National Institute for Statistics and Economic Studies of the Grand Duchy of Luxembourg (STATEC), 13, rue Erasme, 2013, Luxembourg, Luxembourg

    Tatiana Plotnikova

  2. University of Passau, Innstrasse 27, 94032, Passau, Germany

    Bastian Rake

Authors
  1. Tatiana Plotnikova
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Bastian Rake
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Bastian Rake.

Appendices

Appendix 1: List of countries, therapeutic areas and description of variables

See Tables 2, 3, and 4.

Table 2 List of countries
Full size table
Table 3 List of therapeutic areas
Full size table
Table 4 Description of variables
Full size table

Appendix 2: Descriptives, correlations, and additional regressions

See Figs. 2, 3 and Tables 5, 6, and 7.

Fig. 2
figure 2

Share of cross-country collaborations per region

Full size image
Fig. 3
figure 3

Share of cross-country collaborations per income group

Full size image
Table 5 Cross-correlation table without therapeutic areas distinction
Full size table
Table 6 Cross-correlation table with distinguishing therapeutic areas
Full size table
Table 7 Zero-inflated negative binomial regression models without therapeutic area distinction
Full size table

Rights and permissions

Reprints and permissions

About this article

Cite this article

Plotnikova, T., Rake, B. Collaboration in pharmaceutical research: exploration of country-level determinants. Scientometrics 98, 1173–1202 (2014). https://doi.org/10.1007/s11192-013-1182-6

Download citation

  • Received:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11192-013-1182-6

Keywords

Search

Navigation