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Adoption of Information Technology Under Network Effects

Author

Listed:
  • Deishin Lee

    (Harvard Business School, 15 Harvard Way, Morgan Hall 483, Harvard University, Boston, Massachusetts 02163)

  • Haim Mendelson

    (Graduate School of Business, Stanford University, Stanford, California 94305)

Abstract

Because information technologies are often characterized by network effects, compatibility is an important issue. Although total network value is maximized when everyone operates in one compatible network, we find that the technology benefits for the users depend on vendor incentives, which are driven by the existence of “de facto” or “de jure” standards. In head-to-head competition, customers are better off “letting a thousand flowers bloom,” fostering fierce competition that results in a de facto standard if users prefer compatibility over individual fit, or a split market if fit is more important. In contrast, firms that sponsor these products are better off establishing an up-front, de jure standard to lessen the competitive effects of a network market. However, if a firm is able to enter the market first by choosing a proprietary/incompatible technology, it can use a “divide-and-conquer” strategy to increase its profit compared with head-to-head competition, even when there are no switching costs. When there is a first mover, the early adopters, who are “locked in” because of switching costs, never regret their decision to adopt, whereas the late adopters, who are not subject to switching costs, are exploited by the incumbent firm. In head-to-head competition, customers are unified in their preference for incompatibility when there is a first mover; late adopters prefer de jure compatibility because they bear the brunt of the first-mover advantage. This again underscores the interdependence of user net benefits and vendor strategies.

Suggested Citation

  • Deishin Lee & Haim Mendelson, 2007. "Adoption of Information Technology Under Network Effects," Information Systems Research, INFORMS, vol. 18(4), pages 395-413, December.
  • Handle: RePEc:inm:orisre:v:18:y:2007:i:4:p:395-413
    DOI: 10.1287/isre.1070.0138
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    References listed on IDEAS

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    Cited by:

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    2. Manmohan Aseri & Milind Dawande & Ganesh Janakiraman & Vijay S. Mookerjee, 2020. "Ad-Blockers: A Blessing or a Curse?," Information Systems Research, INFORMS, vol. 31(2), pages 627-646, June.
    3. Vicky Gu & Jonathan Davis & Ray Cao & John Vogt, 2017. "The effect of externalities on adoption of social customer relationship management (SCRM)," International Journal of Quality Innovation, Springer, vol. 3(1), pages 1-15, December.
    4. Lucio Fuentelsaz & Juan Pablo Maicas & Yolanda Polo, 2012. "Switching Costs, Network Effects, and Competition in the European Mobile Telecommunications Industry," Information Systems Research, INFORMS, vol. 23(1), pages 93-108, March.
    5. Yifan Dou & D. J. Wu, 2021. "Platform Competition Under Network Effects: Piggybacking and Optimal Subsidization," Information Systems Research, INFORMS, vol. 32(3), pages 820-835, September.
    6. Stefanos Leonardos & Iosif Sakos & Costas Courcoubetis & Georgios Piliouras, 2020. "Catastrophe by Design in Population Games: Destabilizing Wasteful Locked-in Technologies," Papers 2007.12877, arXiv.org.
    7. Jing Wu & He Li & Zhangxi Lin & Haichao Zheng, 2017. "Competition in wearable device market: the effect of network externality and product compatibility," Electronic Commerce Research, Springer, vol. 17(3), pages 335-359, September.
    8. Qiu-Hong Wang & Kai-Lung Hui, 2017. "Technology Mergers and Acquisitions in the Presence of an Installed Base: A Strategic Analysis," Information Systems Research, INFORMS, vol. 28(1), pages 46-63, March.
    9. Roy Jones & Haim Mendelson, 2011. "Information Goods vs. Industrial Goods: Cost Structure and Competition," Management Science, INFORMS, vol. 57(1), pages 164-176, January.
    10. Thomas Koslowski & Jens Strüker, 2011. "ERP On Demand Platform," Business & Information Systems Engineering: The International Journal of WIRTSCHAFTSINFORMATIK, Springer;Gesellschaft für Informatik e.V. (GI), vol. 3(6), pages 359-367, December.
    11. Quan Wang & Beibei Li & Param Vir Singh, 2018. "Copycats vs. Original Mobile Apps: A Machine Learning Copycat-Detection Method and Empirical Analysis," Information Systems Research, INFORMS, vol. 29(2), pages 273-291, June.

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