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Antecedents of Big Data Analytic Adoption and Impacts on Performance: Contingent Effect

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  • Abdalwali Lutfi

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

  • Akif Lutfi Al-Khasawneh

    (Financial and Administrative Sciences Department, AL-Balqa’ Applied University, Irbid University College, Irbid 1293, Jordan
    Financial and Administrative Sciences Department, Institute of Public Administration, Al-Riyadh 11141, Saudi Arabia)

  • Mohammed Amin Almaiah

    (Department of Computer Networks, College of Computer Sciences and Information Technology, King Faisal University, Al-Ahsa 31982, Saudi Arabia
    Faculty of Information Technology, Applied Science Private University, Amman 11931, Jordan
    Department of Computer Science, King Abdullah the II IT School, The University of Jordan, Amman 11942, Jordan)

  • Ahmad Farhan Alshira’h

    (Accounting Department, Faculty of Administrative and Financial Sciences, Irbid National University, Irbid 21110, Jordan)

  • Malek Hamed Alshirah

    (Department of Accounting, Faculty of Economics and Administrative Sciences, Al Al-Bayt University, Al-Mafraq 25113, Jordan)

  • Adi Alsyouf

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

  • Mahmaod Alrawad

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

  • Ahmad Al-Khasawneh

    (Department of Cyber Security, Irbid National University, Irbid 21110, Jordan)

  • Mohamed Saad

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

  • Rommel Al Ali

    (The National Research Center for Creativity and Giftness, King Faisal University, Al Hofuf 31982, Saudi Arabia)

Abstract

The adoption of big data analytics (BDA) is increasing pace both in practice and in theory, owing to the prospects and its potential advantages. Numerous researchers believe that BDA could provide significant advantages, despite constant battles with the constraints that limit its implementation. Here, we suggest an incorporated model to investigate the drivers and impacts of BDA adoption in the Jordanian hotel industry based on the technology–organisation–environment framework and the resource-based view theory. The suggested model incorporates both the adoption and performance components of BDA into a single model. For data collection, in this study, we used an online questionnaire survey. The research model was verified based on responses from 119 Jordanian hotels. This study yielded two significant findings. First, we discovered that relative advantage, organizational readiness, top management support, and government regulations have a major impact on BDA adoption. The study results also reveal a strong and favourable association between BDA adoption and firm performance. Finally, information sharing was found to have a moderating effect on the association between BDA adoption and firm performance. The data revealed how businesses might increase their BDA adoption for improved firm performance. The present study adds to the limited but growing body of literature investigating the drivers and consequences of technology acceptance. The findings of this study can serve as a resource for scholars and practitioners interested in big data adoption in emerging nations.

Suggested Citation

  • Abdalwali Lutfi & Akif Lutfi Al-Khasawneh & Mohammed Amin Almaiah & Ahmad Farhan Alshira’h & Malek Hamed Alshirah & Adi Alsyouf & Mahmaod Alrawad & Ahmad Al-Khasawneh & Mohamed Saad & Rommel Al Ali, 2022. "Antecedents of Big Data Analytic Adoption and Impacts on Performance: Contingent Effect," Sustainability, MDPI, vol. 14(23), pages 1-23, November.
    • Handle: RePEc:gam:jsusta:v:14:y:2022:i:23:p:15516-:d:980355
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