Estimating the Final Size of an Online User Base
AbstractThe 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.
Download InfoIf you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.
Bibliographic InfoPaper provided by University of Waikato, Department of Economics in its series Working Papers in Economics with number 12/15.
Length: 15 pages
Date of creation: 11 Dec 2012
Date of revision:
Contact details of provider:
Postal: Private Bag 3105, Hamilton, New Zealand, 3240
Phone: + 64 (0)7 838 4758 (Administrator)
Fax: + 64 7 838 4331
Web page: http://cms.mngt.waikato.ac.nz/departments/economics
More information through EDIRC
user base growth; Facebook valuation; S-curves;
Find related papers by 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
This paper has been announced in the following NEP Reports:
- NEP-ALL-2013-01-26 (All new papers)
- NEP-MKT-2013-01-26 (Marketing)
- NEP-NET-2013-01-26 (Network Economics)
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
- 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.
- 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.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Brian Silverstone).
If references are entirely missing, you can add them using this form.