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Organizational agility enabled by big data analytics: information systems capabilities view

Youyung Hyun (Department of Global and Interdisciplinary Studies, Hosei University, Chiyoda-ku, Japan)
Jaehyun Park (School of Design, The Hong Kong Polytechnic University, Hung Hom, China)
Taro Kamioka (Graduate School of Business Administration, Hitotsubashi University, Tokyo, Japan)
Younghoon Chang (School of Management and Economics, Beijing Institute of Technology, Beijing, China)

Journal of Enterprise Information Management

ISSN: 1741-0398

Article publication date: 28 March 2023

Issue publication date: 13 June 2023

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Abstract

Purpose

The current study aims to structure the existing knowledge about organizational agility from the information systems (IS) capabilities view and synthesizes how agility is enabled by big data analytics (BDA).

Design/methodology/approach

This study performs a systematic literature review with the lens of IS capabilities view and provides an integrative framework that represents how BDA improves organizational agility through the mediation of IS capabilities.

Findings

This systematic literature review synthesizes what is known and identifies what remains to be further studied with a focus on the relationship between BDA competency and organizational agility, which contributes to academic performance in BDA and agility research communities.

Originality/value

Despite a growing body of literature on the relationship between BDA and agility, a consolidated and systematic understanding of how BDA can enable organizational agility is generally missing. Therefore, the current study addresses this gap by proposing an integrative framework that elucidates the processes in which BDA competency leads to agility through the mediation of IS capabilities.

Keywords

Acknowledgements

Funding: This work was supported by the National Natural Science Foundation of China (Grant No: 72172013, 72110107003).

Citation

Hyun, Y., Park, J., Kamioka, T. and Chang, Y. (2023), "Organizational agility enabled by big data analytics: information systems capabilities view", Journal of Enterprise Information Management, Vol. 36 No. 4, pp. 1032-1055. https://doi.org/10.1108/JEIM-03-2022-0077

Publisher

:

Emerald Publishing Limited

Copyright © 2023, Emerald Publishing Limited

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