Spreading Innovations: Models, Designs and Research Directions

  • Albrecht FritzscheEmail author


Diffusion models are often applied in business and management research to describe the spread of innovations. Regarding the mathematical representation of the process, these models usually remain rather simple—the main challenge is to find the appropriate object of reference, because innovations can be discussed on different levels of detail, from a general purpose technology down to a specific version of a product. Furthermore, contemporary innovations hardly remain static over time, but change their properties in the course of the diffusion process, due to technical updates and changing modes of application. This turns the attention to the question whether companies and public institutions can actually create conditions under which the spread of innovations can be framed as a diffusion process, or if there are other means to make it more predictable and controllable.


  1. 1.
    G. Tarde, The Laws of Imitation (Trans. E. C. Parsons) (Henry Holt, New York, 1903)Google Scholar
  2. 2.
    M. Weber, Economy and Society (University of California Press, Berkeley and Los Angeles, 1978)Google Scholar
  3. 3.
    C. Hubig, Die Kunst des Möglichen I, Technikphilosophie als Reflexion der Medialität, transcript (Bielefeld, 2006)Google Scholar
  4. 4.
    Z. Griliches, Hybrid Corn. Econometrica 25, 501–522 (1957)CrossRefGoogle Scholar
  5. 5.
    M. Gort, S. Klepper, Time paths in the diffusion of product innovations. Econ. J. 92, 630–653 (1982)CrossRefGoogle Scholar
  6. 6.
    E.M. Rogers, Diffusion of Innovations, 4th edn. (The Free Press, New York, 1995)Google Scholar
  7. 7.
    L. Andres, D. Cuberes, M. Diouf, T. Serebrisky, Diffusion of the Internet, A Cross Country Analysis, Working Paper (The World Bank, 2007)Google Scholar
  8. 8.
    M. Jalowski, A. Fritzsche, Ein Rahmenwerk zur Erfassung von IT-Sicherheit als Service-System, in Proceedings of the MKWI, Ilmenau (2016)Google Scholar
  9. 9.
    E. Mansfield, Econometrica 29(4), 741–766 (1961)CrossRefGoogle Scholar
  10. 10.
    P.-F. Verhulst, Notice sur la loi que la population poursuit dans son accroissement. Corresp. Math. Phys. 10, 113–121 (1838)Google Scholar
  11. 11.
    N. Bacaer, A Short History of Mathematical Population Dynamics (Springer, London, 2011)CrossRefzbMATHGoogle Scholar
  12. 12.
    J.C. Fisher, R.H. Pry, Technol. Forecast. Soc. Chang. 2, 75–88 (1971)CrossRefGoogle Scholar
  13. 13.
    ITU, Mobile cellphone subscriptions, Accessed 31 Jan 2016
  14. 14.
    S.C. Bhargava, Technol. Forecast. Soc. Chang. 49, 27–33 (1995)CrossRefGoogle Scholar
  15. 15.
    D. Comin, B. Hobijn, E. Rovito, J. Technol. Transf. 33, 187–207 (2008)CrossRefGoogle Scholar
  16. 16.
    F.D. Davis, A Technology Acceptance Model for Empirically Testing New End-User Information Systems: Theory and Results (Massachusetts Institute of Technology, Boston, 1986)Google Scholar
  17. 17.
    F.D. Davis, Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Q. 13(3), 319–340 (1989)CrossRefGoogle Scholar
  18. 18.
    I. Ajzen, Organ. Behav. Hum. Decis. Process. 50(2), 179–211 (1991)CrossRefGoogle Scholar
  19. 19.
    V. Venkatesh, M.G. Morris, G.B. Davis, F.D. Davis, User acceptance of information technology: toward a unified view. MIS Q. 27(3), 425–478 (2003)CrossRefGoogle Scholar
  20. 20.
    S. Bratzel, Die junge Generation und das Automobil – Neue Kundenanforderungen an das Auto der Zukunft?, in Automotive Management, 2nd edn., ed. by B. Ebel, M.B. Hofer (Springer, Berlin, 2014), pp. 94–110Google Scholar
  21. 21.
    F. Dudenhöffer, Demographie und Innovation. ATZ - Automobiltechnische Zeitschrift 110(1), 62–67 (2008)CrossRefGoogle Scholar
  22. 22.
    H. Becker, Auf Crashkurs, Automobilindustrie im globalen Verdrängungswettbewerb (Springer, Berlin, 2005)Google Scholar
  23. 23.
    C. Zott, R.H. Amit, Lorenzo Massa, J. Manag. 37(4), 1019–1042 (2011)Google Scholar
  24. 24.
    A. Osterwalder, Y. Pigneur, C.L. Tucci, Commun. AIS, 15(5) (2005)Google Scholar
  25. 25.
    R.G. Cooper, Bus. Horiz. May–June 44–53 (1990)Google Scholar
  26. 26.
    F. Piller, C. Ihl, Co-Creation with customers, in Leading Open Innovation, ed. by A.S. Huff, K.M. Möslein, R. Reichwald (MIT Press, Cambridge, 2013), pp. 139–153CrossRefGoogle Scholar
  27. 27.
    H.W. Chesbrough, Open Innovation, The New Imperative for Creating and Profiting from Technology (Harvard Business School Press, Boston, 2003)Google Scholar
  28. 28.
    E. von Hippel, Democratizing Innovation (MIT Press, Boston, 2005)Google Scholar
  29. 29.
    M. O’Hern, A. Rindfleisch, Rev. Market. Res. 6, 94–106 (2008)Google Scholar
  30. 30.
    H. Löfsten, P. Lindelöf, Technovation 25, 1025–1037 (2005)CrossRefGoogle Scholar
  31. 31.
    C.-H. Yang, K. Motohashi, J.-R. Chen, Res. Policy 38(1), 77–85 (2009)CrossRefGoogle Scholar
  32. 32.
    A. Fritzsche, K.M. Möslein, Accelerating Scientific Research with Open Laboratories, British Academy of Management Conference, Portsmouth (2015)Google Scholar
  33. 33.
    A. Roth, A. Fritzsche, J. Jonas, K.M. Möslein, F. Danzinger, Interaktive Kunden als Herausforderung: Die Fallstudie, JOSEPHS® – Die Service-Manufaktur“. HMD Praxis der Wirtschaftsinformatik 51(6), 883–895 (2014)CrossRefGoogle Scholar
  34. 34.
    K.M. Moeslein, A. Fritzsche, The evolution of strategic options, actors, tools and tensions in open innovation, in Strategy and Communication for Innovation, ed. by N. Pfeffermann, J. Gould (Springer, Heidelberg, 2017)Google Scholar

Copyright information

© Springer International Publishing AG 2018

Authors and Affiliations

  1. 1.Institute of Information Management 1, Friedrich-Alexander University Erlangen-NurembergNurembergGermany

Personalised recommendations