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Big Data-Savvy Teams’ Skills, Big Data-Driven Actions and Business Performance

Akhtar, Pervaiz, Frynas, Jędrzej George, Mellahi, Kamel, Ullah, Subhan (2019) Big Data-Savvy Teams’ Skills, Big Data-Driven Actions and Business Performance. British Journal of Management, 30 (2). pp. 252-271. ISSN 1045-3172. (doi:10.1111/1467-8551.12333) (KAR id:75429)

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Official URL
http://dx.doi.org/10.1111/1467-8551.12333

Abstract

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 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 unique data collected from 240 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 multi-disciplinary skills (e.g. computing, mathematics, statistics, machine learning and business domain knowledge) that help them 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 organizations that emphasize BDD actions perform better compared to those that do not focus on such applications and relevant insights.

Item Type: Article
DOI/Identification number: 10.1111/1467-8551.12333
Additional information: Unmapped bibliographic data: DB - Scopus [Field not mapped to EPrints] M3 - Article [Field not mapped to EPrints]
Subjects: H Social Sciences > HF Commerce > HF5351 Business
Divisions: Divisions > Kent Business School - Division > Kent Business School (do not use)
Depositing User: Pervaiz Akhtar
Date Deposited: 26 Jul 2019 09:40 UTC
Last Modified: 08 May 2021 23:00 UTC
Resource URI: https://kar.kent.ac.uk/id/eprint/75429 (The current URI for this page, for reference purposes)
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