IDEAS home Printed from https://ideas.repec.org/a/taf/gmasxx/v44y2020i2p99-127.html
   My bibliography  Save this article

An acceleration-scale model of IING’s diffusion based on force analysis

Author

Listed:
  • Li Wang
  • Chenxiao Wang
  • Qingpu Zhang

Abstract

The diffusion of Internet-based Intangible Network Goods (IINGs) shows new characteristics completely different from that of traditional material products. This paper aims to establish new models to describe and predict IING’s diffusion at the aggregate level. Firstly, we transform the key factors affecting IING’s diffusion into driving forces, resistant forces, and variable forces. Secondly, we analyse the dynamic changes of these forces in different diffusion stages and obtain the acceleration model of IING’s diffusion. Then, since acceleration is the second derivative of scale, we further establish the scale model of IING’s diffusion. As the scale model can predict the number of IING’s adopters at a particular time and the acceleration model can explain the dynamic changes of scale, we combine them as the acceleration-scale model to describe IING’s diffusion. Finally, we make comparisons between the acceleration-scale model and the Bass model based on three cases. Different from the previous studies, we found that IING’s diffusion rate is asymmetric. The diffusion rate of successful IING is right skewed while the diffusion rate of failed IING is left skewed. The results also shows that the acceleration-scale model has a better predictive performance than the Bass model, no matter the diffusion is successful or failed

Suggested Citation

  • Li Wang & Chenxiao Wang & Qingpu Zhang, 2020. "An acceleration-scale model of IING’s diffusion based on force analysis," The Journal of Mathematical Sociology, Taylor & Francis Journals, vol. 44(2), pages 99-127, April.
  • Handle: RePEc:taf:gmasxx:v:44:y:2020:i:2:p:99-127
    DOI: 10.1080/0022250X.2019.1642337
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1080/0022250X.2019.1642337
    Download Restriction: Access to full text is restricted to subscribers.

    File URL: https://libkey.io/10.1080/0022250X.2019.1642337?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    More about this item

    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:taf:gmasxx:v:44:y:2020:i:2:p:99-127. 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.

    We have no bibliographic references for this item. You can help adding them by using 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: Chris Longhurst (email available below). General contact details of provider: http://www.tandfonline.com/gmas .

    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.