Skip to main content
Log in

The co-evolution of knowledge and collaboration networks: the role of the technology life-cycle

  • Published:
Scientometrics Aims and scope Submit manuscript

Abstract

The aim of the paper is to show how the transition from the emergence of a technology to its development phase impacts the evolution of the structure of the collaboration network. In order to identify these first phases of the life cycle of the technology a method is developed based on the International Patent Classification. Using this method, we identify when a technology transitions from an emerging technology to a stage in which applications of the technology are found. We then compare the moment at which this transition occurs to the evolution of the collaboration network for the same technology and show that there is a significant change in the structure of the network when this transition occurs.

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
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8

Similar content being viewed by others

Notes

  1. The ability of firms to absorb and send knowledge also plays an important role.

References

  • Abercrombie, R. K., & Loebl, A. S. (2014). Systems life cycle and its relation with the triple helix. Measuring scholarly impact (pp. 103–125). Springer International Publishing.

  • Abercrombie, R. K., Schlicher, B. G., & Sheldon, F. T. (2015). Scientometric methods for identifying emerging technologies. U.S. Patent No 9,177,249.

  • Abercrombie, R. K., Udoeyop, A. W., & Schlicher, B. G. (2012). A study of scientometric methods to identify emerging technologies via modeling of milestones. Scientometrics, 91(2), 327–342.

    Article  Google Scholar 

  • Ahuja, G. (2000). Collaboration networks, structural holes, and innovation: A longitudinal study. Administrative Science Quarterly, 45(3), 425–455.

    Article  Google Scholar 

  • Alencar, M., Porter, A., & Antunes, A. (2007). Nanopatenting patterns in relation to product life cycle. Technological Forecasting and Social Change, 74(9), 1661–1680.

    Article  Google Scholar 

  • Barabási, A.-L., & Albert, R. (1999). Emergence of scaling in random networks. Science, 286(5439), 509–512.

    Article  MathSciNet  MATH  Google Scholar 

  • Buchmann, T., & Pyka, A. (2013). The evolution of innovation networks: The case of a German automotive network. In FZID Discussion Papers.

  • Gao, L., Porter, A. L., Wang, J., Fang, S., Zhang, X., Ma, T., et al. (2013). Technology life cycle analysis method based on patent documents. Technological Forecasting and Social Change, 80(3), 398–407.

    Article  Google Scholar 

  • Gulati, R., Sytch, M., & Tatarynowicz, A. (2012). The rise and fall of small worlds: Exploring the dynamics of social structure. Organization Science, 23(2), 449–471.

    Article  Google Scholar 

  • McEvily, B., & Marcus, A. (2005). Embedded ties and the acquisition of competitive capabilities. Strategic Management Journal, 26(11), 1033–1055.

    Article  Google Scholar 

  • McKelvey, M., Alm, H., & Riccaboni, M. (2003). Does co-location matter for formal knowledge collaboration in the Swedish biotechnology–pharmaceutical sector? Research Policy, 32(3), 483–501.

    Article  Google Scholar 

  • Owen-Smith, J., & Powell, W. W. (2004). Knowledge networks as channels and conduits: The effects of spillovers in the Boston biotechnology community. Organization Science, 15(1), 5–21.

    Article  Google Scholar 

  • Rosenkopf, L., & Schilling, M. A. (2007). Comparing alliance network structure across industries: Observations and explanations. Strategic Entrepreneurship Journal, 1(3–4), 191–209.

    Article  Google Scholar 

  • Salavisa, I., Sousa, C., & Fontes, M. (2012). Topologies of innovation networks in knowledge-intensive sectors: Sectoral differences in the access to knowledge and complementary assets through formal and informal ties. Technovation, 32(6), 380–399.

    Article  Google Scholar 

  • Saviotti, P. P. (2007). On the dynamics of generation and utilisation of knowledge: The local character of knowledge. Structural Change and Economic Dynamics, 18, 387–408.

    Article  Google Scholar 

  • Shan, W., Walker, G., & Kogut, B. (1994). Interfirm cooperation and startup innovation in the biotechnology industry. Strategic Management Journal, 15(5), 387–394.

    Article  Google Scholar 

  • Stolwijk, C., Ortt, J., & den Hartigh, E. (2013). The joint evolution of alliance networks and technology: A survey of the empirical literature. Technological Forecasting and Social Change, 80(7), 1287–1305.

    Article  Google Scholar 

  • Szulanski, G. (1996). Exploring internal stickiness: imepdiments to the transfer of best practise within the firm. Strategic Management Journal, 17(Special issue), 27–43.

    Article  Google Scholar 

  • Tomasello, M. V., Napoletano, M., Garas, A., & Schweitzer, F. (2013). The rise and fall of R&D networks. ArXiv Preprint ArXiv:1304.3623.

  • Trappey, C. V., Wang, T.-M., Hoang, S., & Trappey, A. J. (2013). Constructing a dental implant ontology for domain specific clustering and life span analysis. Advanced Engineering Informatics, 27(3), 346–357.

    Article  Google Scholar 

  • Tsai, W. (2001). Knowledge transfer in intraorganizational networks: Effects of network position and absorptive capacity on business unit innovation and performance. Academy of Management Journal, 44(5), 996–1004.

    Article  Google Scholar 

  • Uzzi, B., & Spiro, J. (2005). Collaboration and creativity: The small world problem 1. American Journal of Sociology, 111(2), 447–504.

    Article  Google Scholar 

  • Van Der Pol, J. (2015). Structural dynamics of the French aerospace sector: A network analysis. In Working Papers Hal-01284993, HAL.

  • van der Valk, T., Chappin, M. H., & Gijsbers, G. W. (2011). Evaluating innovation networks in emerging technologies. Technological Forecasting and Social Change, 78, 25–39.

    Article  Google Scholar 

  • Verspagen, B., & Duysters, G. (2004). The small worlds of strategic technology alliances. Technovation, 24(7), 563–571.

    Article  Google Scholar 

  • Virapin, D., & Flamand, M. (2013). L’innovation dans les matériaux composites, quelle diffusion autour de quels acteurs?. In Presented at the P2i conference 2013.

  • Watson, J. (2007). Modeling the relationship between networking and firm performance. Journal of Business Venturing, 22(6), 852–874.

    Article  Google Scholar 

  • Watts, D. J., & Strogatz, S. H. (1998). Collective dynamics of ‘small-world’ networks. Nature, 393(4), 440–442.

    Article  MATH  Google Scholar 

Download references

Acknowledgements

The authors are grateful for the financial support from l’Initiative d’Excellence of the University of Bordeaux, the Regional Council of New Aquitaine and the ITEMM Lab financed by Michelin. Comments and suggestions from Murat Yildizoglu, Francesco Lissoni, Bart Verspagen, Thomas Vallée, Andreas Pyka and anonymous referees are gratefully appreciated.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Johannes van der Pol.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

van der Pol, J., Rameshkoumar, JP. The co-evolution of knowledge and collaboration networks: the role of the technology life-cycle. Scientometrics 114, 307–323 (2018). https://doi.org/10.1007/s11192-017-2579-4

Download citation

  • Received:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11192-017-2579-4

Keywords

JEL Classification

Navigation