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An empirical study of the rise of big data in business scholarship

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  • Frizzo-Barker, Julie
  • Chow-White, Peter A.
  • Mozafari, Maryam
  • Ha, Dung

Abstract

Big data has captured the interests of scholars across many disciplines over the last half a decade. Business scholars have increasingly turned their attention to the impact of this emerging phenomenon. Despite the rise in attention, our understanding of what big data is and what it means for organizations and institutional actors remains uncertain. In this study, we conduct a systematic review on “big data” across business scholarship over the past six years (2009–2014). We analyzed 219 peer-reviewed academic papers from 152 journals from the most comprehensive business literature database. We conducted the systematic review both quantitatively and qualitatively using the data analysis software NVivo10. Our results reveal several key insights about the scholarly investigation of big data, including its top benefits and challenges. Overall, we found that big data remains a fragmented, early-stage domain of research in terms of theoretical grounding, methodological diversity and empirically oriented work. These challenges serve to improve our understanding of the state of big data in contemporary research, and to further prompt scholars and decision-makers to advance future research in the most productive manner.

Suggested Citation

  • Frizzo-Barker, Julie & Chow-White, Peter A. & Mozafari, Maryam & Ha, Dung, 2016. "An empirical study of the rise of big data in business scholarship," International Journal of Information Management, Elsevier, vol. 36(3), pages 403-413.
    • Handle: RePEc:eee:ininma:v:36:y:2016:i:3:p:403-413
    DOI: 10.1016/j.ijinfomgt.2016.01.006
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    References listed on IDEAS

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    1. Mohamed Saeudy & Ali Meftah Gerged & Khaldoon Albitar, 2022. "Accounting Perspectives on The Business Value of Big Data During and Beyond The COVID-19 Pandemic," Journal of Accounting and Management Information Systems, Faculty of Accounting and Management Information Systems, The Bucharest University of Economic Studies, vol. 21(2), pages 174-199, June.
    2. Acharya, Abhilash & Singh, Sanjay Kumar & Pereira, Vijay & Singh, Poonam, 2018. "Big data, knowledge co-creation and decision making in fashion industry," International Journal of Information Management, Elsevier, vol. 42(C), pages 90-101.
    3. Calvard, Thomas Stephen & Jeske, Debora, 2018. "Developing human resource data risk management in the age of big data," International Journal of Information Management, Elsevier, vol. 43(C), pages 159-164.
    4. Gupta, Shivam & Kar, Arpan Kumar & Baabdullah, Abdullah & Al-Khowaiter, Wassan A.A., 2018. "Big data with cognitive computing: A review for the future," International Journal of Information Management, Elsevier, vol. 42(C), pages 78-89.
    5. Sebastiano Cupertino & Gianluca Vitale & Angelo Riccaboni, 2018. "L?impatto dei Big Data sulle attivit? di pianificazione & controllo aziendali: In caso di studio di una PMI agricola Italiana," MANAGEMENT CONTROL, FrancoAngeli Editore, vol. 2018(3), pages 59-86.
    6. de Camargo Fiorini, Paula & Roman Pais Seles, Bruno Michel & Chiappetta Jabbour, Charbel Jose & Barberio Mariano, Enzo & de Sousa Jabbour, Ana Beatriz Lopes, 2018. "Management theory and big data literature: From a review to a research agenda," International Journal of Information Management, Elsevier, vol. 43(C), pages 112-129.
    7. Ioannis Margaritis & Michael Madas & Maro Vlachopoulou, 2022. "Big Data Applications in Food Supply Chain Management: A Conceptual Framework," Sustainability, MDPI, vol. 14(7), pages 1-21, March.

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