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Factors Influencing the Adoption of Big Data Analytics in the Digital Transformation Era: Case Study of Jordanian SMEs

Author

Listed:
  • Abdalwali Lutfi

    (Department of Accounting, College of Business, King Faisal University, Al-Ahsa 31982, Saudi Arabia)

  • Adi Alsyouf

    (Department of Managing Health Services and Hospitals, Faculty of Business Rabigh, College of Business (COB), King Abdulaziz University, P.O. Box 344, Jeddah 21991, Saudi Arabia)

  • Mohammed Amin Almaiah

    (Department of Computer Networks, College of Computer Sciences and Information Technology, King Faisal University, Al-Ahsa 31982, Saudi Arabia)

  • Mahmaod Alrawad

    (Quantitative Method Department, College of Business Administration, King Faisal University, Al-Ahsa 31982, Saudi Arabia
    College of Business Administration and Economics, Al-Hussein Bin Talal University, Ma’an 71111, Jordan)

  • Ahmed Abdullah Khalil Abdo

    (Accounting Department, College of Science and Human Studies, Shaqra University, P.O. Box 33, Shaqra 11961, Saudi Arabia
    Accounting Department, Thebes Academy in Saqqara, Saqqara 11434, Egypt)

  • Akif Lutfi Al-Khasawneh

    (Financial & Administrative Sciences Department, Al-Balqa’ Applied University, P.O. Box 50, Al-Huson 21510, Jordan)

  • Nahla Ibrahim

    (Department of Accounting, College of Business, King Faisal University, Al-Ahsa 31982, Saudi Arabia)

  • Mohamed Saad

    (Department of Accounting, College of Business, King Faisal University, Al-Ahsa 31982, Saudi Arabia)

Abstract

Big data (BD) analytics has been increasingly gaining attraction in both practice and theory in light of its opportunities, barriers and expected benefits. In particular, emerging economics view big data analytics as having great importance despite the fact that it has been in a constant struggle with the barriers that prevent its adoption. Thus, this study primarily attempted to determine the drivers of big data analytics in the context of a developing economy, Jordan. The study examined the influence of technological, organizational and environmental factors on big data adoption in the Jordanian SMEs context, using PLS-SEM for the analysis. The empirical results revealed that the relative advantage, complexity, security, top management support, organizational readiness and government support influence the adoption of BD, whilst pressure of competition and compatibility appeared to be of insignificant influence. The findings are expected to contribute to enterprise management and strategic use of data analytics in the present dynamic market environment, for both researcher and practitioner circles concerned with the adoption of big data in developing countries.

Suggested Citation

  • Abdalwali Lutfi & Adi Alsyouf & Mohammed Amin Almaiah & Mahmaod Alrawad & Ahmed Abdullah Khalil Abdo & Akif Lutfi Al-Khasawneh & Nahla Ibrahim & Mohamed Saad, 2022. "Factors Influencing the Adoption of Big Data Analytics in the Digital Transformation Era: Case Study of Jordanian SMEs," Sustainability, MDPI, vol. 14(3), pages 1-17, February.
    • Handle: RePEc:gam:jsusta:v:14:y:2022:i:3:p:1802-:d:742358
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    References listed on IDEAS

    as
    1. Rolando Gonzales & Jonathan Wareham & Jaime Serida, 2015. "Measuring the Impact of Data Warehouse and Business Intelligence on Enterprise Performance in Peru: A Developing Country," Journal of Global Information Technology Management, Taylor & Francis Journals, vol. 18(3), pages 162-187, July.
    2. Maria Ijaz Baig & Liyana Shuib & Elaheh Yadegaridehkordi, 2021. "A Model for Decision-Makers’ Adoption of Big Data in the Education Sector," Sustainability, MDPI, vol. 13(24), pages 1-29, December.
    3. Siti Norida Wahab & Muhammad Iskandar Hamzah & Nazura Mohamed Sayuti & Wei Chern Lee & Say Yik Tan, 2021. "Big data analytics adoption: an empirical study in the Malaysian warehousing sector," International Journal of Logistics Systems and Management, Inderscience Enterprises Ltd, vol. 40(1), pages 121-144.
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