IDEAS home Printed from https://ideas.repec.org/a/bla/bstrat/v34y2025i6p7791-7815.html
   My bibliography  Save this article

Modeling the Role of Big Data Analytics Capabilities in Impacting Corporate Environmental Performance: A Serial Mediation Analysis

Author

Listed:
  • Leul Girma Haylemariam
  • Rana Muhammad Umar
  • Stephen Oduro

Abstract

Big data analytical capabilities (BDAC) have emerged as a significant strategic tool for enhancing environmental performance in today's ever‐growing green and digital economy. However, the serial process through which BDAC influences environmental performance remains understudied, particularly in multinational corporations (MNCs). Drawing on the dynamic capability view (DCV) and the natural resource‐based view (NRBV), this study constructs a serial mediation model to explore the connection between BDAC, ambidextrous green innovation, green competitive advantage, and corporate environmental performance. A cross‐sectional survey involving 244 MNCs in Germany was used for the analysis. The data were analyzed using partial least squares structural equation modeling (PLS‐SEM). Our findings reveal that the impact of BDAC on environmental performance is sequential, occurring through ambidextrous green innovation and the development of green competitive advantage. Specifically, BDAC leads to ambidextrous green innovation, which in turn drives green competitive advantage and ultimately enhances the environmental performance of MNCs. The theoretical and managerial implications are drawn.

Suggested Citation

  • Leul Girma Haylemariam & Rana Muhammad Umar & Stephen Oduro, 2025. "Modeling the Role of Big Data Analytics Capabilities in Impacting Corporate Environmental Performance: A Serial Mediation Analysis," Business Strategy and the Environment, Wiley Blackwell, vol. 34(6), pages 7791-7815, September.
  • Handle: RePEc:bla:bstrat:v:34:y:2025:i:6:p:7791-7815
    DOI: 10.1002/bse.4373
    as

    Download full text from publisher

    File URL: https://doi.org/10.1002/bse.4373
    Download Restriction: no

    File URL: https://libkey.io/10.1002/bse.4373?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
    ---><---

    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:bla:bstrat:v:34:y:2025:i:6:p:7791-7815. 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: Wiley Content Delivery (email available below). General contact details of provider: http://onlinelibrary.wiley.com/journal/10.1002/(ISSN)1099-0836 .

    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.