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Managing network effects in High-Tech Markets

Author

Listed:
  • Jean-Philippe Bonardi

    (UWO - University of Western Ontario)

  • Rodolphe Durand

    (EM - EMLyon Business School)

Abstract

Many high-tech markets are characterized by network effects: situations where consumers make their decisions not simply based on the core product, but also on the quality and availability of its complements. These network effects enable the creation of a technological standard, which can lead to a strong competitive position for the core-product manufacturer. There is no guarantee, however, that this position can be sustained over time. Managers must therefore focus on further developments of the core product. the best way to stimulate further developments may be to reposition the core product in order to strengthen network effects. A three-phase framework can determine how to make an investment in the future generation of a product for which complements are crucial. First, a matrix is provided to evaluate whether the existing technology presents some untapped potential in terms of network effects; second, how to reposition the core product is analyzed; and third, some accompanying measures to manage this repositioning efficiently are suggested.

Suggested Citation

  • Jean-Philippe Bonardi & Rodolphe Durand, 2003. "Managing network effects in High-Tech Markets," Post-Print hal-02311703, HAL.
    • Handle: RePEc:hal:journl:hal-02311703
    DOI: 10.5465/ame.2003.11851827
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    Cited by:

    1. Sebastian Voigt & Oliver Hinz, 2017. "Assessing the economic effects of server launches in free-to-play MMO games," Journal of Business Economics, Springer, vol. 87(4), pages 421-464, May.
    2. Stremersch, S. & Tellis, G.J. & Franses, Ph.H.B.F. & Binken, J.L.G., 2007. "Indirect Network Effects in New Product Growth," ERIM Report Series Research in Management ERS-2007-019-MKT, Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus University Rotterdam.
    3. Chi-Yo Huang & Hui-Ya Wang & Chia-Lee Yang & Steven J. H. Shiau, 2020. "A Derivation of Factors Influencing the Diffusion and Adoption of an Open Source Learning Platform," Sustainability, MDPI, vol. 12(18), pages 1-27, September.
    4. Scott, Susan V. & Van Reenen, John & Zachariadis, Markos, 2017. "The long-term effect of digital innovation on bank performance: An empirical study of SWIFT adoption in financial services," Research Policy, Elsevier, vol. 46(5), pages 984-1004.
    5. Kyungmin Choi & Sunghan Ryu & Daegon Cho, 2019. "When a loss becomes a gain: different effects of substitute versus complementary loss leaders in a multi-sided platform," Electronic Markets, Springer;IIM University of St. Gallen, vol. 29(4), pages 681-691, December.

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