IDEAS home Printed from https://ideas.repec.org/p/wai/econwp/12-15.html
   My bibliography  Save this paper

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

    Download full text from publisher

    File URL: https://repec.its.waikato.ac.nz/wai/econwp/1215.pdf
    Download Restriction: no
    ---><---

    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)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Zal'an Forr'o & Peter Cauwels & Didier Sornette, 2011. "Valuation of Zynga," Papers 1112.6024, arXiv.org.
    2. Fildes, Robert & Kumar, V., 2002. "Telecommunications demand forecasting--a review," International Journal of Forecasting, Elsevier, vol. 18(4), pages 489-522.
    3. Meade, Nigel & Islam, Towhidul, 2006. "Modelling and forecasting the diffusion of innovation - A 25-year review," International Journal of Forecasting, Elsevier, vol. 22(3), pages 519-545.
    4. Kathy A. Paulson Gjerde & Susan A. Slotnick & Matthew J. Sobel, 2002. "New Product Innovation with Multiple Features and Technology Constraints," Management Science, INFORMS, vol. 48(10), pages 1268-1284, October.
    5. Peres, Renana & Muller, Eitan & Mahajan, Vijay, 2010. "Innovation diffusion and new product growth models: A critical review and research directions," International Journal of Research in Marketing, Elsevier, vol. 27(2), pages 91-106.
    6. Davide Arduini & Antonello Zanfei, 2012. "An overview of existing literature on public e-services," Working Papers 1214, University of Urbino Carlo Bo, Department of Economics, Society & Politics - Scientific Committee - L. Stefanini & G. Travaglini, revised 2012.
    7. Parhi, Mamata, 2005. "Diffusion of New Technology in Indian Auto Component Industry: An Examination of the Determinants of Adoption," UNU-INTECH Discussion Paper Series 2005-08, United Nations University - INTECH.
    8. Arduini, Davide & Belotti, Federico & Denni, Mario & Giungato, Gerolamo & Zanfei, Antonello, 2010. "Technology adoption and innovation in public services the case of e-government in Italy," Information Economics and Policy, Elsevier, vol. 22(3), pages 257-275, July.
    9. Liliana Feleaga & Niculae Feleaga & Mihaela Dumitrascu, 2013. "Study On The Perception Of The Corporate Performance In Accounting And Audit Firms," Annals of Faculty of Economics, University of Oradea, Faculty of Economics, vol. 1(1), pages 1316-1323, July.
    10. Christoph Engel & Alon Klement & Karen Weinshall Margel, 2017. "Diffusion of Legal Innovations: The Case of Israeli Class Actions," Discussion Paper Series of the Max Planck Institute for Research on Collective Goods 2017_11, Max Planck Institute for Research on Collective Goods, revised Jan 2018.
    11. Gehringer, Agnieszka, 2016. "Knowledge externalities and sectoral interdependences: Evidence from an open economy perspective," Technological Forecasting and Social Change, Elsevier, vol. 102(C), pages 240-249.
    12. Vardit Landsman & Moshe Givon, 2010. "The diffusion of a new service: Combining service consideration and brand choice," Quantitative Marketing and Economics (QME), Springer, vol. 8(1), pages 91-121, March.
    13. Abedi, Vahideh Sadat, 2019. "Compartmental diffusion modeling: Describing customer heterogeneity & communication network to support decisions for new product introductions," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 536(C).
    14. Marshall, Pablo & Dockendorff, Monika & Ibáñez, Soledad, 2013. "A forecasting system for movie attendance," Journal of Business Research, Elsevier, vol. 66(10), pages 1800-1806.
    15. Inseong Song & Pradeep Chintagunta, 2003. "A Micromodel of New Product Adoption with Heterogeneous and Forward-Looking Consumers: Application to the Digital Camera Category," Quantitative Marketing and Economics (QME), Springer, vol. 1(4), pages 371-407, December.
    16. Chaab, Jafar & Salhab, Rabih & Zaccour, Georges, 2022. "Dynamic pricing and advertising in the presence of strategic consumers and social contagion: A mean-field game approach," Omega, Elsevier, vol. 109(C).
    17. Jie Lu, 2003. "A Model for Evaluating E-Commerce Based on Cost/Benefit and Customer Satisfaction," Information Systems Frontiers, Springer, vol. 5(3), pages 265-277, September.
    18. Malmi, Teemu, 1999. "Activity-based costing diffusion across organizations: an exploratory empirical analysis of Finnish firms," Accounting, Organizations and Society, Elsevier, vol. 24(8), pages 649-672, November.
    19. Ziesemer, Thomas, 1993. "Dynamic Oligopolistic Pricing with Endogenous Change in Market Structure and Market Potential in an Epidemic Diffusion Model," MPRA Paper 61831, University Library of Munich, Germany.
    20. Zhang, Cen & Schmöcker, Jan-Dirk & Kuwahara, Masahiro & Nakamura, Toshiyuki & Uno, Nobuhiro, 2020. "A diffusion model for estimating adoption patterns of a one-way carsharing system in its initial years," Transportation Research Part A: Policy and Practice, Elsevier, vol. 136(C), pages 135-150.

    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

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:wai:econwp:12/15. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Geua Boe-Gibson (email available below). General contact details of provider: https://edirc.repec.org/data/dewaknz.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.