Digital economy challenges and strategies for transforming and upgrading Jilin manufacturing enterprises

Jia Kai (1) , Mohamad Nasir Saludin (2) , Muhammad Omar (3)
(1) Kuala Lumpur University of Science and Technology, China,
(2) Universiti of Geomatika, Malaysia,
(3) Universiti Poly-Tech Malaysia, Malaysia

Abstract

Employee job satisfaction and organizational commitment are vital to workforce stability and service quality in Guangxi’s private universities. In this context, limited resources and heightened performance demands increase the importance of effective leadership. Drawing on self-determination theory and social exchange theory, this study examines how servant leadership influences these work attitudes through employee motivation (Deci & Ryan, 2000; Blau, 1964). Data were collected through a cross-sectional survey of academic and administrative staff (n = 327). The proposed mediation model was analyzed using PLS-SEM in SmartPLS with bootstrapping procedures (Hair et al., 2024). Harman’s single-factor test suggested that common method bias was not a major concern, as the first factor explained 22.66% of the variance (Kock, 2021). The results supported all hypothesized direct effects: servant leadership positively predicted employee motivation, job satisfaction, and organizational commitment, and employee motivation positively predicted job satisfaction and organizational commitment. Bootstrapped mediation analyses further demonstrated significant indirect effects of servant leadership on job satisfaction and organizational commitment via employee motivation. The model accounted for substantial variance in job satisfaction (R² = 0.638) and organizational commitment (R² = 0.586) and showed positive predictive relevance for endogenous constructs (Q² > 0). Overall, the findings provide mechanism-based evidence that employee motivation is a key pathway through which servant leadership enhances important work outcomes in Guangxi private universities, with practical implications for leadership development and human resource management.

Full text article

Generated from XML file

References

Ban, Y., Chen, J., Liu, C., Wang, J., & Liu, J. (2025). Determination of the temporal-spatial pattern distribution and evolution of industrial heritage in Northeast China and its influencing factors via GIS.

Chen, G., Zeng, D., Wei, Q., Zhang, M., & Guo, X. (2020). Decision-making paradigm shift and enabling innovation in the context of big data. Management World, *36*(02), 95–105+220. https://doi.org/10.19744/j.cnki.11-1235/f.2020.0023

Chi, R., Mei, X., & Ruan, H. (2020). How to match intelligent manufacturing with organizational change in SMEs? Research in Science of Science, *38*(07), 1244–1250+1324.

Li, J. (2024). Exploration of enterprise digital transformation from the perspective of corporate governance. China Industry and Information Technology, (04), 1–7. https://doi.org/10.19609/j.cnki.cn10-1299/f.2024.04.003

Li, Y., & Ma, Y. (2022). Research on industrial innovation efficiency and the influencing factors of the old industrial base based on the lock-in effect: A case study of Jilin Province, China. Sustainability, *14*(19), 12739.

Liu, X., & Wang, H. (2023). Industrial Internet and regional manufacturing transformation. China Industrial Economics.

Mancuso, I., Petruzzelli, A. M., & Panniello, U. (2023). Innovating agri-food business models after the Covid-19 pandemic: The impact of digital technologies on the value creation and value capture mechanisms. Technological Forecasting and Social Change, *190*, 122404.

Ministry of Industry and Information Technology of China (MIIT). (2021). 14th Five-Year Plan for Digital Economy Development. https://www.miit.gov.cn/

National Bureau of Statistics of China. (2023). China Statistical Yearbook. https://www.stats.gov.cn/

OECD. (2020). Digital transformation in the manufacturing sector. OECD Publishing. https://www.oecd.org/industry/

Shi, F., Li, X., & Ma, Y. (2023). Research on corporate social responsibility driving model under ESG background. Accounting Monthly, *44*(01), 26–35. https://doi.org/10.19641/j.cnki.42-1290/f.2023.01.004

Su, Y., Zhang, J., & Liu, S. (2023). A review of research on digital transformation, ESG performance and corporate performance. Accounting Monthly, *44*(20), 53–57. https://doi.org/10.19641/j.cnki.42-1290/f.2023.20.007

UNIDO. (2022). Industrial digitalization and inclusive growth. https://www.unido.org/

Vial, G. (2021). Understanding digital transformation: A review and a research agenda. In Managing Digital Transformation (pp. 13–66).

Wang, Y., Wang, T., & Wang, Q. (2024). The impact of digital transformation on enterprise performance: An empirical analysis based on China's manufacturing export enterprises. PLOS ONE, *19*(3), e0299723.

World Bank. (2020). China digital economy development report. https://www.worldbank.org/en/country/china

World Economic Forum. (2021). Global lighthouse network: Digital manufacturing. https://www.weforum.org/

Wu, Y., Li, H., Luo, R., & Yu, Y. (2024). How digital transformation helps enterprises achieve high-quality development? Empirical evidence from Chinese listed companies. European Journal of Innovation Management, *27*(8), 2753–2779.

Zhang, J., & Chen, Y. (2021). Digital economy and manufacturing upgrading in China. Economic Research Journal.

Zhu, X. (2023). Features and spatial effects of urban development and decline in resource-oriented cities: The case of Jilin, China. PLOS ONE, *18*(8), e0289804.

Authors

Jia Kai
Mohamad Nasir Saludin
Muhammad Omar
muhammadomar@uptm.edu.my (Primary Contact)
Kai, J., Saludin, M. N., & Omar, M. (2026). Digital economy challenges and strategies for transforming and upgrading Jilin manufacturing enterprises. The Asian Journal of Professional & Business Studies, 7(1), 279–288. https://doi.org/10.61688/ajpbs.v7i1.501

Article Details

Most read articles by the same author(s)

No Related Submission Found