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Knowledge management technologies and organizational performance: a meta-analytic study

Gang Liu (Business School, Shenzhen Technology University, Shenzhen, China) (Department of Industrial Systems Engineering, Behaviour and Knowledge Engineering (BAKE) Research Centre, The Hong Kong Polytechnic University, Hong Kong, China)
Aino Kianto (School of Business and Management, Lappeenranta-Lahti University of Technology, Lappeenranta, Finland)
Eric Tsui (Department of Industrial Systems Engineering, Behaviour and Knowledge Engineering (BAKE) Research Centre, The Hong Kong Polytechnic University, Hong Kong, China)

Industrial Management & Data Systems

ISSN: 0263-5577

Article publication date: 13 October 2022

Issue publication date: 27 February 2023

436

Abstract

Purpose

This meta-analytic study tries to synthesize the mixed relationships between knowledge management technologies (KMT) and organizational performance as well as aims to explore the impacts of contextual elements, such as national culture, economy and industries, on these relationships.

Design/methodology/approach

Findings on various subjects from 40 previous empirical studies were examined using meta-analysis.

Findings

It was found that KMT are positively related to overall organizational performance as well as financial and nonfinancial performance and that the relationship between KMT and financial performance is stronger in developing economies than in developed economies.

Practical implications

It helps practitioners better understand the role of KMT in organizational performance in various contexts and provides practical suggestions for KMT implementation.

Originality/value

As the first meta-analytic study to address the generalizability of KMT–organizational performance relationships, this paper offers an improved understanding of the benefits of KMT. It also expands knowledge about how contextual issues related to national culture, economies and industries affect KMT payoffs.

Keywords

Acknowledgements

The authors are grateful to the Research Committee of The Hong Kong Polytechnic University for providing a scholarship (project code: RUNQ) to conduct this study.

Citation

Liu, G., Kianto, A. and Tsui, E. (2023), "Knowledge management technologies and organizational performance: a meta-analytic study", Industrial Management & Data Systems, Vol. 123 No. 2, pp. 386-408. https://doi.org/10.1108/IMDS-02-2022-0121

Publisher

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Emerald Publishing Limited

Copyright © 2022, Emerald Publishing Limited

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