Why First Movers May Fail: Global Versus Sequential Improvement of Complex Technological Artefacts

Part of the Springer Proceedings in Complexity book series (SPCOM)

Abstract

We propose a new theory of late mover advantage where new entrants can leapfrog incumbents through introducing new functionality of an existing technology. Since first mover firms did not take into account new functionalities discovered after they entered, they limited their search on older functionalities and find it difficult to optimize functionalities once discovered later on. Late movers, in contrast, do not suffer from such technological irreversibilities, since they only start searching once all functionalities are known. Based on an agent-based model representing the innovation process of a complex technological artifact with a growing number of functionalities, we can conclude that, a first mover disadvantage can appear, particularly when the technology in question is large and complex, as for example in the case of current key technologies such as ICT, energy and mobility systems.

Keywords

First mover advantage Late mover advantage Exaptation Search NK-model Technological evolution Complexity theory 

References

  1. 1.
    Altenberg L (1997) NK fitness landscapes. In: Back T, Fogel D, Michalewicz Z (eds) Handbook of evolutionary computation. Oxford University Press, London Google Scholar
  2. 2.
    Brusoni S, Fontana R (2011) Incumbents’ strategies for platform competition: shaping the boundaries of creative destruction. In: De Liso N, Leoncini R (eds) Internationalization, technological change and the theory of the firm. Routledge, New York, pp 66–88 Google Scholar
  3. 3.
    Ethiraj SK, Levinthal D (2009) Hoping for A to Z while rewarding only A: complex organizations and multiple goals. Organ Sci 20(1):4–21 CrossRefGoogle Scholar
  4. 4.
    Frenken K (2006) Innovation, evolution and complexity theory. Edward Elgar, Cheltenham Glos Google Scholar
  5. 5.
    Ganco M, Hoetker G (2009) NK modeling methodology in the strategy literature: bounded search on a rugged landscape. In: Bergh D, Ketchen D (eds) Research methodology in strategy and management, vol 5. Emerald Group Publishing, Bingley, pp 237–268 Google Scholar
  6. 6.
    Geels FW (2005) Technological transitions and system innovations: a co-evolutionary and socio-technical analysis. Edward Elgar, Cheltenham Glos Google Scholar
  7. 7.
    Kauffman SA (1993) The origins of order: self organization and selection in evolution. Oxford University Press, London Google Scholar
  8. 8.
    Lane DA (2011) Complexity and innovation dynamics. In: Antonelli C (ed) Handbook on the economic complexity of technological change. Edward Elgar, Cheltenham Glos, pp 63–80 Google Scholar
  9. 9.
    van Nierop OA, Blankendaal ACM, Overbeeke CJ (1997) The evolution of the bicycle: a dynamic systems approach. J Des Hist 10(3):253–267 Google Scholar
  10. 10.
    Tushman M, Smith WK, Wood RC, Westerman G, O’Reilly C (2010) Organizational designs and innovation streams. Ind Corp Change 19(5):1331–1366 CrossRefGoogle Scholar
  11. 11.
    West J, Mace M (2010) Browsing as the killer app: explaining the rapid success of Apple’s iPhone. Telecommun Policy 34(5–6):270–286 CrossRefGoogle Scholar

Copyright information

© Springer International Publishing Switzerland 2013

Authors and Affiliations

  1. 1.School of Innovation SciencesEindhoven University of TechnologyEindhovenThe Netherlands

Personalised recommendations