Big data-savvy teams’ skills, big data-driven actions and business performance
Akhtar, Pervaiz; Frynas, Jędrzej George; Mellahi, Kamel; Ullah, Subhan
Jędrzej George Frynas
Dr Subhan Ullah Subhan.Ullah@hull.ac.uk
Lecturer in Accounting and Finance
Prior studies on big data analytics have emphasized the importance of specific big data skills and capabilities for organizational success; however, they have largely neglected to investigate the use of cross-functional teams' skills and its links to the role played by relevant data-driven actions and business performance. Drawing on the resource-based view (RBV) of the firm and on the data collected from big data experts working in global agrifood networks, we examine the links between the use of big data-savvy (BDS) teams' skills, big data-driven (BDD) actions and business performance. BDS teams depend on multidisciplinary skills (e.g., computing, mathematics, statistics, machine learning, and business domain knowledge) that help them to turn their traditional business operations into modern data-driven insights (e.g., knowing real time price changes and customer preferences), leading to BDD actions that enhance business performance. Our results, raised from structural equation modelling, indicate that BDS teams' skills that produce valuable insights are the key determinants for BDD actions, which ultimately contribute to business performance. We further demonstrate that those organisations that emphasise BDD actions perform better compared to those that do not focus on such applications and relevant insights.
|Journal Article Type||Article|
|Journal||British Journal of Management|
|Peer Reviewed||Not Peer Reviewed|
|APA6 Citation||Akhtar, P., Frynas, J. G., Mellahi, K., & Ullah, S. (2019). Big data-savvy teams’ skills, big data-driven actions and business performance. British Journal of Management, 30(2), 252-271. https://doi.org/10.1111/1467-8551.12333|
|Keywords||Big data-savvy teams; big data multidisciplinary skills; big data-driven actions; resource-based view; business performance 2|
This file is under embargo until May 1, 2021 due to copyright restrictions.
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