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Understanding the Determinants of Big Data Adoption in India: An Analysis of the Manufacturing and Services Sectors

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  • Hemlata Gangwar

    (Pune Institute of Business Management, Pune, India)

Abstract

This article sought to identify the drivers of Big Data adoption within the manufacturing and services sectors in India. A questionnaire-based survey was used to collect data from manufacturing and service sector organizations in India. The data was analyzed using exploratory and confirmatory factor analyses. Relevant hypotheses were then derived and tested by SEM analysis. The findings revealed that the following factors are important for both sectors: relative advantage, compatibility, complexity, organizational size, top management support, competitive pressure, vendor support, data management and data privacy. Statistically significant differences between the service and the manufacturing sectors were found. In other words, the relative importance of the factors for Big Data adoption differs between the sectors. The only exception was complexity, which was found to be insignificant in regard to the manufacturing sector. The factors identified can be used to facilitate Big Data adoption outcomes in organizations.

Suggested Citation

  • Hemlata Gangwar, 2018. "Understanding the Determinants of Big Data Adoption in India: An Analysis of the Manufacturing and Services Sectors," Information Resources Management Journal (IRMJ), IGI Global, vol. 31(4), pages 1-22, October.
    • Handle: RePEc:igg:rmj000:v:31:y:2018:i:4:p:1-22
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    Cited by:

    1. Ebrahim A. A. Ghaleb & P. D. D. Dominic & Suliman Mohamed Fati & Amgad Muneer & Rao Faizan Ali, 2021. "The Assessment of Big Data Adoption Readiness with a Technology–Organization–Environment Framework: A Perspective towards Healthcare Employees," Sustainability, MDPI, vol. 13(15), pages 1-33, July.
    2. 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.
    3. 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.
    4. Huihui Liu & Hui Yu & Hongmin Zhou & Xiantang Zhang, 2023. "Research on the Influencing Factors of Construction Enterprises’ Digital Transformation Based on DEMATEL-TAISM," Sustainability, MDPI, vol. 15(12), pages 1-22, June.
    5. Amit Kumar & Bala Krishnamoorthy, 2020. "Business Analytics Adoption in Firms: A Qualitative Study Elaborating TOE Framework in India," International Journal of Global Business and Competitiveness, Springer, vol. 15(2), pages 80-93, December.
    6. Xuejun Jin & Xiao Pan, 2023. "Government Attention, Market Competition and Firm Digital Transformation," Sustainability, MDPI, vol. 15(11), pages 1-27, June.
    7. Lei, Zhimei & Chen, Yandan & Lim, Ming K., 2021. "Modelling and analysis of big data platform group adoption behaviour based on social network analysis," Technology in Society, Elsevier, vol. 65(C).
    8. 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.
    9. Abdalwali Lutfi & Hamza Alqudah, 2023. "The Influence of Technological Factors on the Computer-Assisted Audit Tools and Techniques Usage during COVID-19," Sustainability, MDPI, vol. 15(9), pages 1-22, May.
    10. Thamir Hamad Alaskar, 2023. "Innovation Capabilities as a Mediator between Business Analytics and Firm Performance," Sustainability, MDPI, vol. 15(6), pages 1-20, March.
    11. Ebrahim A. A. Ghaleb & P. D. D. Dominic & Narinderjit Singh Sawaran Singh & Gehad Mohammed Ahmed Naji, 2023. "Assessing the Big Data Adoption Readiness Role in Healthcare between Technology Impact Factors and Intention to Adopt Big Data," Sustainability, MDPI, vol. 15(15), pages 1-25, July.

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