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The interplay of soft TQM practices and knowledge sharing: moderating role of market turbulence

Ai-Fen Lim, Keng-Boon Ooi, Voon-Hsien Lee, Garry Wei-Han Tan

Industrial Management & Data Systems

ISSN: 0263-5577

Article publication date: 15 August 2022

Issue publication date: 8 November 2022

520

Abstract

Purpose

Emerging competitive dynamics demand small and medium-sized enterprises (SMEs) to continuously comprehend and respond to changing market conditions by implementing effective soft total quality management (STQM) practices. Firstly, the study intends to identify the key STQM practices perceived to foster knowledge sharing (KS). Secondly, this study aims to investigate the impact of market turbulence (MT) on the interaction between STQM practices and KS among SMEs.

Design/methodology/approach

A total of 215 valid samples were analysed. Incorporating a two-hidden-layer deep artificial neural network (ANN) into SEM approaches allows for more in-depth testing and high prediction power. This study employs a two-stage PLS-SEM-ANN predictive-analytical technique to provide a more comprehensive analysis and significant statistical contribution.

Findings

The PLS-SEM-ANN analysis reveals that STQM practices including employee involvement (EI), employee training (ET), top management commitment (TMC) and employee teamwork (EM) are critical to boosting KS. MT, interestingly, moderates the relationship between EM and KS while negatively moderating the relationship between TMC and KS.

Originality/value

The study contributes to the knowledge-based view theory by demonstrating the importance of integrating STQM and KS among SMEs to thrive in today's dynamic market environment.

Keywords

Acknowledgements

This research is part of the author’s PhD works and was conducted while the author is a Ph.D. candidate at UCSI Graduate Business School, UCSI University.

Citation

Lim, A.-F., Ooi, K.-B., Lee, V.-H. and Tan, G.W.-H. (2022), "The interplay of soft TQM practices and knowledge sharing: moderating role of market turbulence", Industrial Management & Data Systems, Vol. 122 No. 11, pp. 2440-2464. https://doi.org/10.1108/IMDS-09-2021-0562

Publisher

:

Emerald Publishing Limited

Copyright © 2022, Emerald Publishing Limited

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