Unlocking the drivers of big data analytics value in firms

Nadine Côrte-Real, Pedro Ruivo, Tiago Oliveira and Aleš Popovič

Journal of Business Research, 2019, vol. 97, issue C, 160-173

Abstract: Although big data analytics (BDA) is considered the next “frontier” in data science by creating potential business opportunities, the way to extract those opportunities is unclear. This paper aims to understand the antecedents of BDA value at a firm level. The authors performed a study using a mixed methodology approach. First, by carrying out a Delphi study to explore and rank the antecedents affecting the creation of BDA value. Based on the Delphi results, we propose an empirically validated model supported by a survey conducted on 175 European firms to explain the antecedents of BDA sustained value. The results show that the proposed model explains 62% of BDA sustained value at the firm level, where the most critical contributor is BDA use. We provide directions for managers to support their decisions on BDA strategy definition and refinement. For academics, we extend BDA value literature and outline some potential research opportunities.

Keywords: IT business value; Big data analytics (BDA); Delphi method; Mixed methodology; Competitive advantage (search for similar items in EconPapers)
Date: 2019
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (21)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:jbrese:v:97:y:2019:i:c:p:160-173

DOI: 10.1016/j.jbusres.2018.12.072

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