Advanced Search
MyIDEAS: Login to save this article or follow this journal

Innovation Diffusion in a Dynamic Potential Adopter Population


Author Info

  • Vijay Mahajan

    (Ohio State University)

  • Robert A. Peterson

    (University of Texas at Austin)

Registered author(s):


    Existing single-adoption diffusion models assume a static (constant) ceiling on the number of adopters, that is, a constant population of potential adopters, over the entire time frame of the diffusion process. However, for most innovations this assumption is tenuous. Rather, the ceiling, or the potential adopter population is more likely to be dynamic. The present paper relaxes this assumption and presents a dynamic diffusion model. To illustrate the application of this model, data from two innovations are analyzed.

    Download Info

    If 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.
    File URL:
    Download Restriction: no

    Bibliographic Info

    Article provided by INFORMS in its journal Management Science.

    Volume (Year): 24 (1978)
    Issue (Month): 15 (November)
    Pages: 1589-1597

    as in new window
    Handle: RePEc:inm:ormnsc:v:24:y:1978:i:15:p:1589-1597

    Contact details of provider:
    Postal: 7240 Parkway Drive, Suite 300, Hanover, MD 21076 USA
    Phone: +1-443-757-3500
    Fax: 443-757-3515
    Web page:
    More information through EDIRC

    Related research

    Keywords: marketing; marketing: buyer behavior; health care: epidemiology;


    No references listed on IDEAS
    You can help add them by filling out this form.


    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as in new window

    Cited by:
    1. Luigi De Cesare & Andrea Di Liddo & Stefania Ragni, 2003. "Numerical Solutions to Some Optimal Control Problems Arising from Innovation Diffusion," Computational Economics, Society for Computational Economics, vol. 22(2), pages 173-186, October.
    2. Martin Hewing, 2012. "A Theoretical and Empirical Comparison of Innovation Diffusion Models Applying Data from the Software Industry," Journal of the Knowledge Economy, Springer, vol. 3(2), pages 125-141, June.
    3. Francesco Bogliacino & Giorgio Rampa, 2009. "Quality Risk Aversion, Conjectures, and New Product Diffusion," Quaderni di Dipartimento 092, University of Pavia, Department of Economics and Quantitative Methods.
    4. Yann Duval & Arlo Biere, 2001. "Product diffusion and the demand for new food products," Agribusiness, John Wiley & Sons, Ltd., vol. 18(1), pages 23-36.
    5. Chih-Jou Chen & Chia-Chin Chang & Shiu-Wan Hung, 2011. "Influences of Technological Attributes and Environmental Factors on Technology Commercialization," Journal of Business Ethics, Springer, vol. 104(4), pages 525-535, December.
    6. Kim, Namwoon & Srivastava, Rajendra K., 2007. "Modeling cross-price effects on inter-category dynamics: The case of three computing platforms," Omega, Elsevier, vol. 35(3), pages 290-301, June.
    7. Crompton, Paul, 2001. "The diffusion of new steelmaking technology," Resources Policy, Elsevier, vol. 27(2), pages 87-95, June.
    8. Fuentelsaz, Lucio & Gomez, Jaime & Polo, Yolanda, 2003. "Intrafirm diffusion of new technologies: an empirical application," Research Policy, Elsevier, vol. 32(4), pages 533-551, April.
    9. Sadou, Karim, 2002. "L’impact des externalités de réseau sur le processus de décision du consommateur," Economics Papers from University Paris Dauphine 123456789/5855, Paris Dauphine University.
    10. Kalika, Michel & Pallud, Jessie & Elie-dit-Cosaque, Christophe, 2008. "The Influence of Work Environment On It-Specific Individual Differences: An Empirical Study," Economics Papers from University Paris Dauphine 123456789/8266, Paris Dauphine University.
    11. Pablo Marshall, 2000. "Difusion De Internet En Chile," Abante, Escuela de Administracion. Pontificia Universidad Católica de Chile., vol. 3(2), pages 143-163.
    12. Luigi De Cesare & Andrea Di Liddo & Stefania Ragni, 2002. "Numerical solution of some optimal control problems arising from innovation diffusion," Computing in Economics and Finance 2002 221, Society for Computational Economics.
    13. de Bondt, Gabe & Marqués-Ibáñez, David, 2004. "The high-yield segment of the corporate bond market: a diffusion modelling approach for the United States, the United Kingdom and the euro area," Working Paper Series 0313, European Central Bank.


    This item is not listed on Wikipedia, on a reading list or among the top items on IDEAS.


    Access and download statistics


    When requesting a correction, please mention this item's handle: RePEc:inm:ormnsc:v:24:y:1978:i:15:p:1589-1597. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Mirko Janc).

    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 references are entirely missing, you can add them using this form.

    If the full references list an item that is present in RePEc, but the system did not link 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 profile, as there may be some citations waiting for confirmation.

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