IDEAS home Printed from https://ideas.repec.org/a/jle/joujqt/ktve2753.html

Why E-Commerce Startups Fail: can machine learning provide solution?

Author

Listed:
  • Mona Yadegar

    (UCSI University, Malaysia.)

Abstract

E-commerce has transformed how businesses operate, providing customers with convenience and companies with access to global markets. However, despite its vast potential, many e-commerce initiatives have failed due to either external conditions such as local or global market fluctuations or internal conditions such as a mixture of poor planning, financial mismanagement, operational inefficiencies, and cybersecurity risks. Focusing on the market fluctuations which is a key component for external conditions. A simulative dataset that mimics real-world market conditions is used to present contribution of machine learning to decision making stages. The usage of informatics could help mitigate these risks by improving decision-making, security, and operational efficiency, and in turn could prevented many of the failures.

Suggested Citation

  • Mona Yadegar, 2025. "Why E-Commerce Startups Fail: can machine learning provide solution?," Journal of Quantum Technologies and Informatics Research, Holistence Publications, vol. 3(1), pages 2753-2753.
    • Handle: RePEc:jle:joujqt:ktve2753
    DOI: 10.70447/ktve.2753
    as

    Download full text from publisher

    To our knowledge, this item is not available for download. To find whether it is available, there are three options:
    1. Check below whether another version of this item is available online.
    2. Check on the provider's web page whether it is in fact available.
    3. Perform a
    for a similarly titled item that would be available.

    More about this item

    Keywords

    ;
    ;
    ;
    ;
    ;

    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:jle:joujqt:ktve2753. 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: Cumali Yasar (email available below). General contact details of provider: https://journals.gen.tr/index.php/jqtair .

    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.