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Cited by 260Big Data and Business IntelligenceInformation Technology Governance and StrategyInnovation and Knowledge Management

The role of information governance in big data analytics driven innovation

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Mikalef, Patrick, Boura, Maria, Lekakos, George, Krogstie, John·2020·Information & Management
DOI 10.1016/j.im.2020.103361
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Abstract

The age of big data analytics is now here, with companies increasingly investing in big data initiatives to foster innovation and outperform competition. Nevertheless, while researchers and practitioners started to examine the shifts that these technologies entail and their overall business value, it is still unclear whether and under what conditions they drive innovation. To address this gap, this study draws on the resource-based view (RBV) of the firm and information governance theory to explore the interplay between a firm’s big data analytics capabilities (BDACs) and their information governance practices in shaping innovation capabilities. We argue that a firm’s BDAC helps enhance two distinct types of innovative capabilities, incremental and radical capabilities, and that information governance positively moderates this relationship. To examine our research model, we analyzed survey data collected from 175 IT and business managers. Results from partial least squares structural equation modelling analysis reveal that BDACs have a positive and significant effect on both incremental and radical innovative capabilities. Our analysis also highlights the important role of information governance, as it positively moderates the relationship between BDAC’s and a firm’s radical innovative capability, while there is a nonsignificant moderating effect for incremental innovation capabilities. Finally, we examine the effect of environmental uncertainty conditions in our model and find that information governance and BDACs have amplified effects under conditions of high environmental dynamism.

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Research works printed but not linked: 7

  1. S. Ransbotham, D. Kiron, Analytics as a Source of Business Innovation, MIT Sloan Management Review, 2017.
  2. P. Mikalef, I.O. Pappas, J. Krogstie, M. Giannakos, Big data analytics capabilities: a systematic literature review and research agenda, Inf. Syst. E-business Manag. (2017) 1-32.
  3. J. Nunnally, Psychometric Methods, McGraw-Hill, New York, 1978.
  4. Patrick Mikalef is an associate professor in Data Science and Information Systems at the Department of Computer Science. In the past, he has been a Marie Skłodowska-Curie postdoctoral research fellow working on the research project "Competitive Advantage for the Data-driven Enterprise" (CADENT). He received his B.Sc. in Informatics from the Ionian University, his M.Sc. in Business Informatics for Utrecht University, and his Ph.D. in IT Strategy from the Ionian University. His research interests focus on the strategic use of information systems and IT-business value in turbulent environments. He has published work in international conferences and peer-reviewed journals including the European Journal of Information Systems, Journal of Business Research, British Journal of Management, Information and Management, and European Journal of Operational Research.
  5. Maria Boura is a postdoctoral researcher at the Department of Management Science and Technology of the Athens University of Economics and Business. Her research interests focus on Business Strategy, Corporate Social Responsibility, Business Ethics and Corruption, and Big data and management. Her research papers have been published in international academic conferences (the Academy of Management, European Academy of Management, British Academy of Management, European Group for Organisational Studies, and European Conference on Information Systems). She holds a Ph.D. and an M.Sc. from the Athens University of Economics and Business (Greece).
  6. eltrun.gr) at the Athens University of Economics and Business (AUEB), Greece. His re- search focuses on Machine learning, Recommender Systems, Big Data and Strategy, and e- business. He has published more than sixty papers in international journals and con- ferences (e.g., EJOR, International Journal of Electronic Commerce, User Modelling and User adapted interaction, etc.), and he is coeditor of books, conference proceedings, journals' special issues and serves as editorial board member of international journals.
  7. John Krogstie holds a Ph.D. (1995) and an M.Sc. (1991) in information systems from the Norwegian University of Science and Technology (NTNU), where he is currently a full professor in information systems at the computer science department (IDI). At IDI he is Department Head. John Krogstie is the Norwegian representative and previously Vice- Chair for IFIP TC8 and was chair of IFIP WG 8.1 on information system design and evaluations (2010-2015). His research interests are information systems modelling, in- formation systems engineering, quality of models and modelling languages, eGovernment and mobile information systems. He has published around 300 refereed papers in jour- nals, books, and archival proceedings since 1991. H-index as of August 2020 is 45 and G- index 69 according to Google Scholar.

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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
ORCID
Venue
Information & Management
Publisher
Elsevier BV
Published
2020-11
Volume
57
Issue
7
Pages
103361
ISSN
0378-7206 (ISSN-L)
DOI
10.1016/j.im.2020.103361
OpenAlex
W3049164745
Cited by
260
References
106
Citations by year
2026: 30 · 2025: 51 · 2024: 63 · 2023: 44 · 2022: 44 · 2021: 26 · 2020: 2
FWCI
32.94
Type
journal article
Language
en
Open access
Licence
Locations
  • Information & Management (publishedVersion, cc-by)
  • NORA - Norwegian Open Research Archives (submittedVersion, cc-by)
Funders
Athens University of Economics and Business
Topics
  • Social Sciences › Business, Management and Accounting › Management Information Systems › Big Data and Business Intelligence
  • Social Sciences › Business, Management and Accounting › Management Information Systems › Information Technology Governance and Strategy
  • Social Sciences › Business, Management and Accounting › Strategy and Management › Innovation and Knowledge Management
Keywords
information governance, big data analytics capability, innovation ability, incremental innovation, radical innovation, resource-based view, environmental uncertainty, environmental dynamism, moderating effect, big data analytics

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