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Big Data Analytics Capabilities and Innovation: The Mediating Role of Dynamic Capabilities and Moderating Effect of the Environment
Open accessAbstract
Abstract With big data analytics growing rapidly in popularity, academics and practitioners have been considering the means through which they can incorporate the shifts these technologies bring into their competitive strategies. Drawing on the resource‐based view, the dynamic capabilities view, and on recent literature on big data analytics, this study examines the indirect relationship between a big data analytics capability (BDAC) and two types of innovation capabilities: incremental and radical. The study extends existing research by proposing that BDACs enable firms to generate insight that can help strengthen their dynamic capabilities, which in turn positively impact incremental and radical innovation capabilities. To test their proposed research model, the authors used survey data from 175 chief information officers and IT managers working in Greek firms. By means of partial least squares structural equation modelling, the results confirm the authors’ assumptions regarding the indirect effect that BDACs have on innovation capabilities. Specifically, they find that dynamic capabilities fully mediate the effect on both incremental and radical innovation capabilities. In addition, under conditions of high environmental heterogeneity, the impact of BDACs on dynamic capabilities and, in sequence, incremental innovation capability is enhanced, while under conditions of high environmental dynamism the effect of dynamic capabilities on incremental innovation capabilities is amplified.
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Metadata
- Authors
- Mikalef, P., Boura, M., Lekakos, G., & Krogstie, J.
- Affiliations
- Norwegian University of Science and Technology (NO)
- Athens University of Economics and Business (GR)
- Corresponding author
- Mikalef, Patrick
- Venue
- British Journal of Management
- Publisher
- Wiley
- Published
- 2019-04
- Volume
- 30
- Issue
- 2
- Pages
- 272-298
- ISSN
- 1045-3172 (ISSN-L)
- 1467-8551
- OpenAlex
- W2944471258
- Cited by
- 835
- References
- 128
- Citations by year
- 2026: 130 · 2025: 154 · 2024: 157 · 2023: 156 · 2022: 106 · 2021: 83 · 2020: 33 · 2019: 16
- FWCI
- 79.22
- Type
- journal article
- Language
- en
- Open access
- green
- hdl.handle.net
- Licence
- Locations
- British Journal of Management (publishedVersion)
- NORA - Norwegian Open Research Archives (submittedVersion, other-oa)
- Funders
- European Union's Horizon 2020
- Marie Sklodowska-Curie (No 704110)
- Topics
- Social Sciences › Business, Management and Accounting › Management Information Systems › Big Data and Business Intelligence
- Social Sciences › Business, Management and Accounting › Strategy and Management › Innovation and Knowledge Management
- Social Sciences › Decision Sciences › Information Systems and Management › Big Data Technologies and Applications
- Keywords
- big data analytics capability, dynamic capabilities, incremental innovation, radical innovation, innovation ability, environmental heterogeneity, environmental dynamism, mediating effect, moderating effect, resource-based view, competitive strategy, chief information officer
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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