IDEAS home Printed from https://ideas.repec.org/a/wly/mgtdec/v45y2024i1p300-314.html
   My bibliography  Save this article

Unleashing the power of big data for platform firms: A configuration analysis

Author

Listed:
  • Zhen Wang
  • Chunhui Yuan
  • Xiaolong Li

Abstract

This study investigates the impact of big data on platform performance using a multidimensional perspective and the fuzzy set qualitative comparative analysis (fsQCA) method. We identify two pathways for platforms to leverage big data to achieve performance improvement: “volume‐centric configuration” and “volume‐talent synergistic configuration.” Our results indicate that big data volume and talent of big data are the core conditions impacting platform performance, but an increase in these factors does not always equate to an improvement in performance. The study makes two substantial contributions: (1) identifying the configurations of big data that lead to high performance of the platform and illuminating the complex interplay of causality between the multidimensional nature of big data resources and their supporting conditions and (2) measuring the multidimensionality of big data resources in platform firms through the utilization of operational data of the app in question. This study has significant practical implications, providing guidance to platform firms on identifying appropriate big data resources to gain a competitive advantage and utilizing supporting conditions to address deficiencies in data assets.

Suggested Citation

  • Zhen Wang & Chunhui Yuan & Xiaolong Li, 2024. "Unleashing the power of big data for platform firms: A configuration analysis," Managerial and Decision Economics, John Wiley & Sons, Ltd., vol. 45(1), pages 300-314, January.
  • Handle: RePEc:wly:mgtdec:v:45:y:2024:i:1:p:300-314
    DOI: 10.1002/mde.4000
    as

    Download full text from publisher

    File URL: https://doi.org/10.1002/mde.4000
    Download Restriction: no

    File URL: https://libkey.io/10.1002/mde.4000?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:wly:mgtdec:v:45:y:2024:i:1:p:300-314. 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://www3.interscience.wiley.com/cgi-bin/jhome/7976 .

    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.