IDEAS home Printed from https://ideas.repec.org/a/igg/rmj000/v32y2019i3p1-26.html
   My bibliography  Save this article

Understanding the Determinants of Big Data Analytics Adoption

Author

Listed:
  • Surabhi Verma

    (NMIMS, Navi Mumbai, India)

  • Sushil Chaurasia

    (NMIMS, Navi Mumbai, India)

Abstract

This article aims to empirically investigate the factors that affects the adoption of big data analytics by firms (adopters and non-adopters). The current study is based on three feature that influence BDA adoption: technological context (relative advantage, complexity, compatibility), organizational context (top management support, technology readiness, organizational data environment), and environmental context (competitive pressure, and trading partner pressure). A structured questionnaire-based survey method was used to collect data from 231 firm managers. Relevant hypotheses were derived and tested by partial least squares. The results indicated that technology, organization and environment contexts impact firms' adoption of big data analytics. The findings also revealed that relative advantage, complexity, compatibility, top management support, technology readiness, organizational data environment and competitive pressure have a significant influence on the adopters of big data analytics, whereas relative advantage, complexity and competitive pressure have a significant influence on the non-adopters of big data analytics.

Suggested Citation

  • Surabhi Verma & Sushil Chaurasia, 2019. "Understanding the Determinants of Big Data Analytics Adoption," Information Resources Management Journal (IRMJ), IGI Global, vol. 32(3), pages 1-26, July.
    • Handle: RePEc:igg:rmj000:v:32:y:2019:i:3:p:1-26
    as

    Download full text from publisher

    File URL: http://services.igi-global.com/resolvedoi/resolve.aspx?doi=10.4018/IRMJ.2019070101
    Download Restriction: no
    ---><---

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Shafique, Muhammad Noman & Yeo, Sook Fern & Tan, Cheng Ling, 2024. "Roles of top management support and compatibility in big data predictive analytics for supply chain collaboration and supply chain performance," Technological Forecasting and Social Change, Elsevier, vol. 199(C).
    2. Luther Yuong Qai Chong & Thien Sang Lim, 2022. "Pull and Push Factors of Data Analytics Adoption and Its Mediating Role on Operational Performance," Sustainability, MDPI, vol. 14(12), pages 1-19, June.
    3. Abdalwali Lutfi & Ahmad Farhan Alshira’h & Malek Hamed Alshirah & Manaf Al-Okaily & Hamza Alqudah & Mohamed Saad & Nahla Ibrahim & Osama Abdelmaksoud, 2022. "Antecedents and Impacts of Enterprise Resource Planning System Adoption among Jordanian SMEs," Sustainability, MDPI, vol. 14(6), pages 1-18, March.
    4. Luay Jum’a & Muhammad Ikram & Ziad Alkalha & Maher Alaraj, 2022. "Do Companies Adopt Big Data as Determinants of Sustainability: Evidence from Manufacturing Companies in Jordan," Global Journal of Flexible Systems Management, Springer;Global Institute of Flexible Systems Management, vol. 23(4), pages 479-494, December.
    5. Thamir Hamad Alaskar & Amin K. Alsadi, 2023. "Drivers of mobile commerce adoption intention by Saudi SMEs during the COVID-19 pandemic," Future Business Journal, Springer, vol. 9(1), pages 1-13, December.
    6. Thamir Hamad Alaskar, 2023. "Innovation Capabilities as a Mediator between Business Analytics and Firm Performance," Sustainability, MDPI, vol. 15(6), pages 1-20, March.

    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:igg:rmj000:v:32:y:2019:i:3:p:1-26. 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: Journal Editor (email available below). General contact details of provider: https://www.igi-global.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.