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First mover or higher quality? Optimal product strategy in markets with positive feedbacks

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  • P.J. Lamberson
  • Scott E. Page

Abstract

Conventional wisdom holds that in markets with positive feedbacks being first to market can matter more than product quality. In this paper, we test that intuition within a generalized Pólya urn model. We find that if we assume constant feedbacks, in the long run, higher quality products dominate the market regardless of initial market shares, contradicting the common wisdom. However, when we allow for variable feedbacks, initial advantages persist almost indefinitely. Thus, the choice of whether to rush to market or focus on quality depends on market characteristics such as whether the positive feedbacks result from more consistent returns to scale or from more variable social influences.

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  • P.J. Lamberson & Scott E. Page, 2018. "First mover or higher quality? Optimal product strategy in markets with positive feedbacks," Journal of Economics & Management Strategy, Wiley Blackwell, vol. 27(1), pages 40-52, March.
  • Handle: RePEc:bla:jemstr:v:27:y:2018:i:1:p:40-52
    DOI: 10.1111/jems.12231
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    Cited by:

    1. Tolotti, Marco & Yepez, Jorge, 2020. "Hotelling-Bertrand duopoly competition under firm-specific network effects," Journal of Economic Behavior & Organization, Elsevier, vol. 176(C), pages 105-128.
    2. Jay Pil Choi & Christodoulos Stefanadis, 2022. "Network Externalities, Dominant Value Margins, And Equilibrium Uniqueness," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 63(4), pages 1805-1827, November.
    3. P. J. Lamberson, 2018. "Approximating individual interactions in compartmental system dynamics models," System Dynamics Review, System Dynamics Society, vol. 34(1-2), pages 284-326, January.
    4. Chang, Sungyong & Park, Sanghyun, 2021. "Borders of Network Effects and Early Internationalization as a Latecomer Strategy," SocArXiv d74he, Center for Open Science.

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