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A Punctuated-Equilibrium Model of Technology Diffusion

Author

Listed:
  • Christoph H. Loch

    (INSEAD, Boulevard de Constance, 77305 Fontainebleau Cedex, France)

  • Bernardo A. Huberman

    (Xerox PARC, Palo Alto, California 94304)

Abstract

We present an evolutionary model of technology diffusion in which an old and a new technology are available, both of which improve their performance incrementally over time. Technology adopters make repeated choices between the established and the new technology based on their perceived performance, which is subject to uncertainty. Both technologies exhibit positive externalities, or performance benefits from others using the same technology. We find that the superior technology will not necessarily be broadly adopted by the population. Externalities cause two stable usage equilibria to exist, one with the old technology being the standard and the other with the new technology the standard. Punctuations, or sudden shifts, in these equilibria determine the patterns of technology diffusion. The time for an equilibrium punctuation depends on the rate of incremental improvement of both technologies, and on the system's resistance to switching between equilibria. If the new technology has a higher rate of incremental improvement, it is adopted faster, and adoption may precede performance parity if the system's resistance to switching is low. Adoption of the new technology may trail performance parity if the system's resistance to switching is high.

Suggested Citation

  • Christoph H. Loch & Bernardo A. Huberman, 1999. "A Punctuated-Equilibrium Model of Technology Diffusion," Management Science, INFORMS, vol. 45(2), pages 160-177, February.
  • Handle: RePEc:inm:ormnsc:v:45:y:1999:i:2:p:160-177
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    File URL: http://dx.doi.org/10.1287/mnsc.45.2.160
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    References listed on IDEAS

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    Citations

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    Cited by:

    1. Zhang, T. & Nuttall, W.J., 2007. "An Agent Based Simulation Of Smart Metering Technology Adoption," Cambridge Working Papers in Economics 0760, Faculty of Economics, University of Cambridge.
    2. Stephan Aier & Tobias Bucher & Robert Winter, 2011. "Critical Success Factors of Service Orientation in Information Systems Engineering," Business & Information Systems Engineering: The International Journal of WIRTSCHAFTSINFORMATIK, Springer;Gesellschaft für Informatik e.V. (GI), vol. 3(2), pages 77-88, April.
    3. Bonaccorsi, Andrea & Rossi, Cristina, 2003. "Why Open Source software can succeed," Research Policy, Elsevier, vol. 32(7), pages 1243-1258, July.
    4. Tieju Ma, 2010. "Coping with Uncertainties in Technological Learning," Management Science, INFORMS, vol. 56(1), pages 192-201, January.
    5. Rui Leite & Aurora Teixeira, 2012. "Innovation diffusion with heterogeneous networked agents: a computational model," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 7(2), pages 125-144, October.
    6. José López-Sánchez & José Arroyo-Barrigüete & Domingo Ribeiro, 2008. "Development of a technological competition model in the presence of network effects from the modified law of Metcalfe," Service Business, Springer;Pan-Pacific Business Association, vol. 2(2), pages 83-98, June.
    7. Yair Orbach & Gila Fruchter, 2014. "Predicting product life cycle patterns," Marketing Letters, Springer, vol. 25(1), pages 37-52, March.
    8. Scott A. Shane & Karl T. Ulrich, 2004. "50th Anniversary Article: Technological Innovation, Product Development, and Entrepreneurship in Management Science," Management Science, INFORMS, vol. 50(2), pages 133-144, February.
    9. Fildes, Robert & Kumar, V., 2002. "Telecommunications demand forecasting--a review," International Journal of Forecasting, Elsevier, vol. 18(4), pages 489-522.
    10. Costa, Álvaro & Fernandes, Ruben, 2012. "Urban public transport in Europe: Technology diffusion and market organisation," Transportation Research Part A: Policy and Practice, Elsevier, vol. 46(2), pages 269-284.
    11. Uwe Cantner & Simone Vannuccini, 2017. "Innovation and lock-in," Chapters,in: The Elgar Companion to Innovation and Knowledge Creation, chapter 11, pages 165-181 Edward Elgar Publishing.
    12. Antonelli, Cristiano, 2007. "The system dynamics of collective knowledge: From gradualism and saltationism to punctuated change," Journal of Economic Behavior & Organization, Elsevier, vol. 62(2), pages 215-236, February.
    13. Carrillo-Hermosilla, Javier, 2006. "A policy approach to the environmental impacts of technological lock-in," Ecological Economics, Elsevier, vol. 58(4), pages 717-742, July.
    14. Narayanan, V.K. & Chen, Tianxu, 2012. "Research on technology standards: Accomplishment and challenges," Research Policy, Elsevier, vol. 41(8), pages 1375-1406.
    15. Dutta, Amitava & Puvvala, Abhinay & Roy, Rahul & Seetharaman, Priya, 2017. "Technology diffusion: Shift happens — The case of iOS and Android handsets," Technological Forecasting and Social Change, Elsevier, vol. 118(C), pages 28-43.
    16. Warr, Benjamin & Ayres, Robert, 2006. "REXS: A forecasting model for assessing the impact of natural resource consumption and technological change on economic growth," Structural Change and Economic Dynamics, Elsevier, vol. 17(3), pages 329-378, September.
    17. Rajiv D. Banker & Robert J. Kauffman, 2004. "50th Anniversary Article: The Evolution of Research on Information Systems: A Fiftieth-Year Survey of the Literature in Management Science," Management Science, INFORMS, vol. 50(3), pages 281-298, March.
    18. Liangjie Zhao & Wenqi Duan, 2014. "Simulating the Evolution of Market Shares: The Effects of Customer Learning and Local Network Externalities," Computational Economics, Springer;Society for Computational Economics, vol. 43(1), pages 53-70, January.
    19. Papachristos, George, 2017. "Diversity in technology competition: The link between platforms and sociotechnical transitions," Renewable and Sustainable Energy Reviews, Elsevier, vol. 73(C), pages 291-306.
    20. Grajek, Michał & Kretschmer, Tobias, 2012. "Identifying critical mass in the global cellular telephony market," International Journal of Industrial Organization, Elsevier, vol. 30(6), pages 496-507.
    21. Orbach Yair & Fruchter Gila E., 2010. "A Utility-Based Diffusion Model Applied to the Digital Camera Case," Review of Marketing Science, De Gruyter, vol. 8(1), pages 1-28, June.
    22. Armstrong, Michael J & Levesque, Moren, 2002. "Timing and quality decisions for entrepreneurial product development," European Journal of Operational Research, Elsevier, vol. 141(1), pages 88-106, August.
    23. Christoph H. Loch & Stylianos Kavadias, 2002. "Dynamic Portfolio Selection of NPD Programs Using Marginal Returns," Management Science, INFORMS, vol. 48(10), pages 1227-1241, October.
    24. Minniti, Maria, 2004. "Entrepreneurial alertness and asymmetric information in a spin-glass model," Journal of Business Venturing, Elsevier, vol. 19(5), pages 637-658, September.
    25. Mudambi, Ram & Swift, Tim, 2011. "Proactive R&D management and firm growth: A punctuated equilibrium model," Research Policy, Elsevier, vol. 40(3), pages 429-440, April.

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