IDEAS home Printed from https://ideas.repec.org/a/pal/jmarka/v12y2024i1d10.1057_s41270-023-00252-4.html
   My bibliography  Save this article

I will buy virtual goods if I like them: a hybrid PLS-SEM-artificial neural network (ANN) analytical approach

Author

Listed:
  • Nadjim Mkedder

    (University of Abou Bekr Belkaid Tlemcen)

  • Fatma Zeynep Özata

    (Anadolu University)

Abstract

Despite the popularity of Free-to-Play (F2P) games in recent years, the motivations behind players’ intention to purchase virtual goods in F2P games still require further investigations. This study aims to address this dilemma by investigating the antecedents of functional, emotional, and social values in shaping the purchase intention of virtual goods in F2P games. Using purposive sampling, data were collected through a survey from 352 F2P game participants in the United States. A hybrid PLS-SEM-Artificial Neural Network (ANN) modeling approach was employed to examine the impact of these factors on the intention to purchase virtual goods. The results reveal that perceived value positively influences the purchase intention of virtual goods. The findings also show that functional, emotional, and social values significantly impact the perceived value and purchase intention of virtual goods. Further, perceived value mediates the relationship between quality, achievement, enjoyment, aesthetics, customization, self-presentation, and the intention to purchase virtual goods. The ANN results reveal that quality and social presence are the most critical factors since they achieve the greatest normalized importance ratio compared to the others. The model illustrated considerable explanatory evidence for purchase intention in the context of F2P games. Additionally, this research significantly strengthens the marketing literature by developing an understanding of the intention to buy virtual goods in F2P games. The proposed model can provide insights for F2P game providers to design their games and marketing strategies.

Suggested Citation

  • Nadjim Mkedder & Fatma Zeynep Özata, 2024. "I will buy virtual goods if I like them: a hybrid PLS-SEM-artificial neural network (ANN) analytical approach," Journal of Marketing Analytics, Palgrave Macmillan, vol. 12(1), pages 42-70, March.
  • Handle: RePEc:pal:jmarka:v:12:y:2024:i:1:d:10.1057_s41270-023-00252-4
    DOI: 10.1057/s41270-023-00252-4
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1057/s41270-023-00252-4
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.

    File URL: https://libkey.io/10.1057/s41270-023-00252-4?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.

    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:pal:jmarka:v:12:y:2024:i:1:d:10.1057_s41270-023-00252-4. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.palgrave-journals.com/ .

    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.