IDEAS home Printed from https://ideas.repec.org/a/taf/ecinnt/v26y2017i7p621-633.html
   My bibliography  Save this article

Estimating demand function parameters of mobile applications

Author

Listed:
  • Michael Scholz

Abstract

The vibrant market for mobile applications has raised awareness of several professional and also voluntary software developers. The key question especially for professional developers is how to improve the profit gained with a developed app. Recent research provided evidence on the factors that determine the demand of a mobile app. This paper presents a procedure to estimate demand function parameters that are required for developing pricing, advertising and also product update strategies. More specifically, the procedure estimates an app’s maximal willingness to pay, demand elasticity on price and network value. The procedure is based on the Fulfilled Expectations Cournot Model and requires knowledge about the apps being considered as substitutes to each other. It is applied to a data set consisting of download rank data of Apple iPhone apps.

Suggested Citation

  • Michael Scholz, 2017. "Estimating demand function parameters of mobile applications," Economics of Innovation and New Technology, Taylor & Francis Journals, vol. 26(7), pages 621-633, October.
  • Handle: RePEc:taf:ecinnt:v:26:y:2017:i:7:p:621-633
    DOI: 10.1080/10438599.2017.1263444
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1080/10438599.2017.1263444
    Download Restriction: Access to full text is restricted to subscribers.

    File URL: https://libkey.io/10.1080/10438599.2017.1263444?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:ecinnt:v:26:y:2017:i:7:p:621-633. 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/GEIN20 .

    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.