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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
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    File URL: http://services.igi-global.com/resolvedoi/resolve.aspx?doi=10.4018/IRMJ.2019070101
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    Cited by:

    1. 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.
    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. 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).
    5. 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.
    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.

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