Building data-driven dynamic capabilities to arrest knowledge hiding: A knowledge management perspective

Yantai Chen, Haibei Luo, Jin Chen and Yanlin Guo

Journal of Business Research, 2022, vol. 139, issue C, 1138-1154

Abstract: In this study, the authors have conducted a multiple-case study on four Chinese enterprises in different industries, to explore how to build data-driven dynamic capabilities from the perspective of knowledge management, with a focus on how to arrest knowledge hiding. This research constructs a comprehensive theoretical framework of “data-driven context – dynamic capabilities – knowledge hiding,” proposing three dimensions of “institutional environment – organizational innovation – executive/individual cognition” on building dynamic capabilities, with original contributions on expanding and enriching knowledge hiding theory and dynamic capabilities theory in the data-driven context. As for practical implications, this research provides guidance on how to build dynamic capabilities to arrest or mitigate knowledge hiding for executives or individuals in the workplace, and gives enlightenment to how firms in emerging economies can construct dynamic capabilities in the data-driven context.

Keywords: Knowledge hiding; Knowledge management; Data-driven; Dynamic capabilities (search for similar items in EconPapers)
Date: 2022
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Citations: View citations in EconPapers (5)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:jbrese:v:139:y:2022:i:c:p:1138-1154

DOI: 10.1016/j.jbusres.2021.10.050

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