IDEAS home Printed from https://ideas.repec.org/a/aza/airwa0/y2024v3i2p111-123.html
   My bibliography  Save this article

The theoretical potential of algorithmic and automated pricing to increase company value

Author

Listed:
  • Rathnow, Peter

    (Owner, Prof. Rathnow Consulting, Germany)

  • Zeller, Benjamin

    (Manager Corporate Strategy, Ivoclar Vivadent, Liechtenstein)

  • Lederer, Matthias

    (OTH Technical University of Applied Sciences Amberg-Weiden, Germany)

Abstract

This paper explores the potential benefits and challenges of algorithmic and automated pricing for businesses and critically examines the associated ethical and legal implications. To this end, in this first part of a two-part study, seven areas of discussion were identified in which the future of algorithmic pricing can be described in an overall view (eg data, resource allocation). Within these areas, a total of nine central hypotheses (eg what effects it will have on competitive situations and the development of user acceptance) were developed on the basis of current scientific findings. The overall study takes a customer-centric approach and proposes that algorithmic pricing should be seen not only as a tool to maximise profits, but as a strategy that creates added value for both the company and the consumer. In the second part of the study (to be published in the next issue of the journal), the hypotheses developed in this paper will be evaluated by experts in the field.

Suggested Citation

  • Rathnow, Peter & Zeller, Benjamin & Lederer, Matthias, 2024. "The theoretical potential of algorithmic and automated pricing to increase company value," Journal of AI, Robotics & Workplace Automation, Henry Stewart Publications, vol. 3(2), pages 111-123, March.
  • Handle: RePEc:aza:airwa0:y:2024:v:3:i:2:p:111-123
    as

    Download full text from publisher

    File URL: https://hstalks.com/article/8572/download/
    Download Restriction: Requires a paid subscription for full access.

    File URL: https://hstalks.com/article/8572/
    Download Restriction: Requires a paid subscription for full access.
    ---><---

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

    More about this item

    Keywords

    algorithmic pricing; dynamic pricing; shareholder value; customer centricity; profit maximisation; value creation;
    All these keywords.

    JEL classification:

    • M15 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Business Administration - - - IT Management
    • G2 - Financial Economics - - Financial Institutions and Services

    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:aza:airwa0:y:2024:v:3:i:2:p:111-123. 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: Henry Stewart Talks (email available below). General contact details of provider: .

    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.