research-article

Factors influencing effective use of big data: : A research framework

Authors:

Feliks P. Sejahtera Surbakti,

Marta Indulska,

Shazia SadiqAuthors Info & Claims

Volume 57, Issue 1

https://doi.org/10.1016/j.im.2019.02.001

Published: 01 January 2020 Publication History

Highlights

•

Comprehensive review of the literature relating to the effective use of big data.

•

Identification of 7 themes, from the current body of literature.

•

We propose a framework and highlight research areas that require attention.

Abstract

Information systems (IS) research has explored “effective use” in a variety of contexts. However, it is yet to specifically consider it in the context of the unique characteristics of big data. Yet, organizations have a high appetite for big data, and there is growing evidence that investments in big data solutions do not always lead to the derivation of intended value. Accordingly, there is a need for rigorous academic guidance on what factors enable effective use of big data. With this paper, we aim to guide IS researchers such that the expansion of the body of knowledge on the effective use of big data can proceed in a structured and systematic manner and can subsequently lead to empirically driven guidance for organizations. Namely, with this paper, we cast a wide net to understand and consolidate from literature the potential factors that can influence the effective use of big data, so they may be further studied. To do so, we first conduct a systematic literature review. Our review identifies 41 factors, which we categorize into 7 themes, namely data quality; data privacy and security and governance; perceived organizational benefit; process management; people aspects; systems, tools, and technologies; and organizational aspects. To explore the existence of these themes in practice, we then analyze 45 published case studies that document insights into how specific companies use big data successfully. Finally, we propose a framework for the study of effective use of big data as a basis for future research. Our contributions aim to guide researchers in establishing the relevance and relationships within the identified themes and factors and are a step toward developing a deeper understanding of effective use of big data.

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Gao JSarwar Z(2024)How do firms create business value and dynamic capabilities by leveraging big data analytics management capability?Information Technology and Management10.1007/s10799-022-00380-w25:3(283-304)Online publication date: 1-Sep-2024
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Bandara FJayawickrama USubasinghage MOlan FAlamoudi HAlharthi M(2024)Enhancing ERP Responsiveness Through Big Data Technologies: An Empirical InvestigationInformation Systems Frontiers10.1007/s10796-023-10374-w26:1(251-275)Online publication date: 1-Feb-2024
https://dl.acm.org/doi/10.1007/s10796-023-10374-w
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Factors influencing effective use of big data: A research framework
1. Information systems
2. Social and professional topics

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Information & Contributors

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cover image Information and Management

Information and Management Volume 57, Issue 1

Jan 2020

122 pages

ISSN:0378-7206

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Elsevier B.V.

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Elsevier Science Publishers B. V.

Netherlands

Publication History

Published: 01 January 2020

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Fromm JStieglitz SMirbabaie M(2024)Virtual Reality in Digital Education: An Affordance Network Perspective on Effective Use BehaviorACM SIGMIS Database: the DATABASE for Advances in Information Systems10.1145/3663682.366368555:2(14-41)Online publication date: 3-May-2024
https://dl.acm.org/doi/10.1145/3663682.3663685
Gao JSarwar Z(2024)How do firms create business value and dynamic capabilities by leveraging big data analytics management capability?Information Technology and Management10.1007/s10799-022-00380-w25:3(283-304)Online publication date: 1-Sep-2024
https://dl.acm.org/doi/10.1007/s10799-022-00380-w
Bandara FJayawickrama USubasinghage MOlan FAlamoudi HAlharthi M(2024)Enhancing ERP Responsiveness Through Big Data Technologies: An Empirical InvestigationInformation Systems Frontiers10.1007/s10796-023-10374-w26:1(251-275)Online publication date: 1-Feb-2024
https://dl.acm.org/doi/10.1007/s10796-023-10374-w
Zarefard MMarsden N(2024)The Essential Competencies of Data Scientists: A Framework for Hiring and TrainingHuman Interface and the Management of Information10.1007/978-3-031-60125-5_27(397-418)Online publication date: 29-Jun-2024
https://dl.acm.org/doi/10.1007/978-3-031-60125-5_27
Solaimani SSwaak L(2023)Critical Success Factors in a multi-stage adoption of Artificial IntelligenceJournal of Engineering and Technology Management10.1016/j.jengtecman.2023.10176069:COnline publication date: 1-Jul-2023
https://dl.acm.org/doi/10.1016/j.jengtecman.2023.101760
Truong N(2022)Factors Affecting Big Data AdoptionInternational Journal of Asian Business and Information Management10.4018/IJABIM.31582513:1(1-21)Online publication date: 1-Sep-2022
https://dl.acm.org/doi/10.4018/IJABIM.315825
Dlugosch OBrandt TNeumann D(2022)Combining analytics and simulation methods to assess the impact of shared, autonomous electric vehicles on sustainable urban mobilityInformation and Management10.1016/j.im.2020.10328559:5Online publication date: 1-Jul-2022
https://dl.acm.org/doi/10.1016/j.im.2020.103285
Ranjan JForopon C(2022)Big Data Analytics in Building the Competitive Intelligence of OrganizationsInternational Journal of Information Management: The Journal for Information Professionals10.1016/j.ijinfomgt.2020.10223156:COnline publication date: 22-Apr-2022
https://dl.acm.org/doi/10.1016/j.ijinfomgt.2020.102231
Leso BCortimiglia M(2022)The influence of user involvement in information system adoption: an extension of TAMCognition, Technology and Work10.1007/s10111-021-00685-w24:2(215-231)Online publication date: 1-May-2022
https://dl.acm.org/doi/10.1007/s10111-021-00685-w
Sadiq SAryani ADemartini GHua WIndulska MBurton-Jones AKhosravi HBenavides-Prado DSellis TSomeh IVaithianathan RWang SZhou X(2022)Information Resilience: the nexus of responsible and agile approaches to information useThe VLDB Journal — The International Journal on Very Large Data Bases10.1007/s00778-021-00720-231:5(1059-1084)Online publication date: 1-Sep-2022
https://dl.acm.org/doi/10.1007/s00778-021-00720-2
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