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Estimating the Final Size of an Online User Base

Author

Listed:
  • Steven Lim

    (University of Waikato)

Abstract
The theoretical insights from the increasing returns literature, plus the interaction between consumers facilitated by networked technologies, have led to a synthesis in which virtual communities become uniquely valuable to an online firm. Strategy in social media markets, in particular, becomes one of promoting information sharing and connectivity within networks of user communities, deepening the relationship between the user base and sellers, and paving the way for a revenue payoff. When network externalities also suggest the possibility of barriers to entry and lock-in operating on the demand side, the importance of a large user base correspondingly increases. From a finance perspective the relevant question then is: how large will a firm’s user base eventually become? Cauwels and Sornette (2011) answer this question by positing an S-shaped model of user growth. We extend their model by introducing competition from another online firm. With this extension, S-shaped growth is altered, potentially invalidating Cauwels and Sornette’s (2011) results.

Suggested Citation

  • Steven Lim, 2012. "Estimating the Final Size of an Online User Base," Working Papers in Economics 12/15, University of Waikato.
    • Handle: RePEc:wai:econwp:12/15
    as

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    File URL: https://repec.its.waikato.ac.nz/wai/econwp/1215.pdf
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    References listed on IDEAS

    as
    1. Peter CAUWELS & Didier SORNETTE, 2011. "Quis pendit ipsa pretia: facebook valuation and diagnostic of a bubble based on nonlinear demographic dynamics," Swiss Finance Institute Research Paper Series 11-58, Swiss Finance Institute.
    2. Rabik Ar Chatterjee & Jehoshua Eliashberg, 1990. "The Innovation Diffusion Process in a Heterogeneous Population: A Micromodeling Approach," Management Science, INFORMS, vol. 36(9), pages 1057-1079, September.
    3. Peter Cauwels & Didier Sornette, 2011. "Quis pendit ipsa pretia: facebook valuation and diagnostic of a bubble based on nonlinear demographic dynamics," Papers 1110.1319, arXiv.org, revised Nov 2011.
    4. Peter CAUWELS & Didier SORNETTE, 2011. "Quis pendit ipsa pretia: facebook valuation and diagnostic of a bubble based on nonlinear demographic dynamics," Swiss Finance Institute Research Paper Series 11-59, Swiss Finance Institute.
    5. Oecd, 2001. "The Internet and Business Performance," OECD Digital Economy Papers 57, OECD Publishing.
    6. Rui Baptista, 1999. "The Diffusion of Process Innovations: A Selective Review," International Journal of the Economics of Business, Taylor & Francis Journals, vol. 6(1), pages 107-129.
    Full references (including those not matched with items on IDEAS)

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    More about this item

    Keywords

    user base growth; Facebook valuation; S-curves;
    All these keywords.

    JEL classification:

    • C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: General
    • D85 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Network Formation
    • G17 - Financial Economics - - General Financial Markets - - - Financial Forecasting and Simulation

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