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Ambidextrous knowledge accumulation, dynamic capability and manufacturing digital transformation in China

Yong Qi ( School of Intellectual Property, Nanjing University of Science and Technology, Nanjing, China)
Qian Chen ( School of Intellectual Property, Nanjing University of Science and Technology, Nanjing, China)
Mengyuan Yang ( School of Intellectual Property, Nanjing University of Science and Technology, Nanjing, China) ( School of Finance, Yunnan University of Finance and Economics, Kunming, China)
Yilei Sun ( School of Economics, Yunnan University of Finance and Economics, Kunming, China)

Journal of Knowledge Management

ISSN: 1367-3270

Article publication date: 9 April 2024

Issue publication date: 10 October 2024

623

Abstract

Purpose

Existing studies have paid less attention to the impact of knowledge accumulation on digital transformation and its boundary conditions. Hence, this study aims to investigate the effects of ambidextrous knowledge accumulation on manufacturing digital transformation under the moderation of dynamic capability.

Design/methodology/approach

This study divides knowledge accumulation into exploratory and exploitative knowledge accumulation and divides dynamic capability into alliance management capability and new product development capability. To clarify the relationship among ambidextrous knowledge accumulation, dynamic capability and manufacturing digital transformation, the authors collect data from 421 Chinese listed manufacturing enterprises from 2016 to 2020 and perform analysis by multiple hierarchical regression method, heterogeneity test and robustness analysis.

Findings

The empirical results show that both exploratory and exploitative knowledge accumulation can significantly promote manufacturing digital transformation. Keeping ambidextrous knowledge accumulation in parallel is more conducive than keeping single-dimensional knowledge accumulation. Besides, dynamic capability positively moderates the relationship between ambidextrous knowledge accumulation and manufacturing digital transformation. Moreover, the heterogeneity test shows that the impact of ambidextrous knowledge accumulation and dynamic capabilities on manufacturing digital transformation varies widely across different industry segments or different regions.

Originality/value

First, this paper shifts attention to the role of ambidextrous knowledge accumulation in manufacturing digital transformation and expands the connotation and extension of knowledge accumulation. Second, this study reveals that dynamic capability is a vital driver of digital transformation, which corroborates the previous findings of dynamic capability as an important driver and contributes to enriching the knowledge management literature. Third, this paper provides a comprehensive micro measurement of ambidextrous knowledge accumulation and digital transformation based on the development characteristics of the digital economy era, which provides a theoretical basis for subsequent research.

Keywords

Acknowledgements

This work was supported by National Natural Science Foundation of China: [Grant Number 71974096]; National Social Science Fund of China: [Grant Number 22VRC064]; Postgraduate Research and Practice Innovation Program of Jiangsu Province: [Grant Number KYCX23_0613]; Youth Project of Philosophy and Social Science Planning in Yunnan Province: [Grant Number QN202212].

Yong Qi and Qian Chen have contributed equally to this work and should be considered co-first authors.

Conflict of interest statement: The authors declare that they have no financial and personal relationships with other people or organizations that can inappropriately influence our work, and there is no professional or other personal interest of any nature or kind in any product, service and/or company.

Citation

Qi, Y., Chen, Q., Yang, M. and Sun, Y. (2024), "Ambidextrous knowledge accumulation, dynamic capability and manufacturing digital transformation in China", Journal of Knowledge Management, Vol. 28 No. 8, pp. 2275-2305. https://doi.org/10.1108/JKM-09-2022-0717

Publisher

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Emerald Publishing Limited

Copyright © 2024, Emerald Publishing Limited

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