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The influence mechanism of enterprise digitalization on employee taking charge

Shengmin Liu & Pengfan Cheng

International Journal of Manpower2025https://doi.org/10.1108/ijm-05-2024-0316article
AJG 2ABDC A
Weight
0.48

Abstract

Purpose The proactive activities, as well as the traditional management mode of enterprises, have undergone profound changes in response to the wave of digital transformation. Consequently, understanding the impact of enterprise digitalization on employee taking charge and its underlying influence mechanisms has become a crucial topic for organizational researchers to explore. Taking a self-determination perspective, this study aims to investigate the mechanism through which enterprise digitalization influences employee taking charge. Design/methodology/approach To achieve this objective, using multi-level structural equation model and bootstrapping, the study collected multi-source data from 358 samples from 30 technology enterprises. Findings These results reveal that enterprise digitalization exerts a significant positive effect on employee taking charge via three parallel mediators of job autonomy, self-efficacy and closeness with companions. Originality/value Overall, the study expands upon the relationship between enterprise digitalization and employee challenge behaviors while offering valuable insights for implementing enterprise digitalization initiatives and facilitating employees' absorption of digitized practices.

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https://doi.org/https://doi.org/10.1108/ijm-05-2024-0316

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@article{shengmin2025,
  title        = {{The influence mechanism of enterprise digitalization on employee taking charge}},
  author       = {Shengmin Liu & Pengfan Cheng},
  journal      = {International Journal of Manpower},
  year         = {2025},
  doi          = {https://doi.org/https://doi.org/10.1108/ijm-05-2024-0316},
}

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Evidence weight

0.48

Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40

F · citation impact0.41 × 0.4 = 0.16
M · momentum0.63 × 0.15 = 0.09
V · venue signal0.50 × 0.05 = 0.03
R · text relevance †0.50 × 0.4 = 0.20

† Text relevance is estimated at 0.50 on the detail page — for your query’s actual relevance score, open this paper from a search result.