The Impact of Data-Driven Management on Decision Consistency in Firms: Evidence from Chinese Manufacturing and Service Sectors

Authors

  • Zhuoer Chen

DOI:

https://doi.org/10.54097/q63m2g11

Keywords:

Data-Driven Management, Decision Consistency, Organizational Performance, Chinese Firms, Decision-Making Quality

Abstract

The study determines how data-driven management (DDM) affects decisions at Chinese companies operating in manufacturing and service industries. With the growing complexity of the market environment and the demands of digital transformation that Chinese enterprises are facing, steady and quality decision-making has become one of the key success factors of competitive advantage. DDM, as a systematic data collection system with sophisticated analytics potential and evidence-based decision-making processes, has a promising potential to improve the quality and consistency of organizational decisions. This research aims to explore the effect of DDM practices on decision consistency at various organizational levels and the mechanisms by which the relationship between the two works out. The research design is a mixed-methods research design, which combines the qualitative analysis of a case study of top Chinese companies and the quantitative analysis of 180 listed companies based on regression. The results indicate that DDM has a substantial positive influence on decision consistency, where firms with a high intensity of DDM exhibit 42 percent increased decision alignment and a 35 percent decrease in decision variance compared to low DDM adopters. The study finds the concept of digital maturity as one of the factors of the moderation multiplier that strengthens the positive impacts of DDM on decision consistency. Moreover, this research reveals the implementation issues related to the Chinese business environment, such as cultural reluctance to data-focused methods and the inability to integrate with the old systems. The study adds to the current body of knowledge because it gives empirical evidence of the relationship between DDM and decision consistency in the Chinese institutional context and offers practical suggestions to companies that aim to increase the quality of decision-making by using systematic data.

Downloads

Download data is not yet available.

References

[1] Wang, Y. (2025). Algorithmic decision-making in organizations: A systematic review toward an integrated tension alignment framework. Organization Management Journal. https://doi.org/10.1108/OMJ-11-2024-2342

[2] Mordor Intelligence. (2025). China management consulting services market: size, share & growth trends report. Retrieved February 16, 2026, from https://www.mordorintelligence.com/industry-reports/china-management-consulting-services-market

[3] Li, F. (2025). The relationship between digital transformation and organisational efficiency in China: The mediating role of information disclosure. Sage Open, 15(3), 1–19. https://doi.org/10.1177/21582440251360487

[4] Joseph, J., & Sengul, M. (2025). Organization design: Current insights and future research directions. Journal of Management, 51(1), 249–308. https://doi.org/10.1177/0149206324127124

[5] Pu, Y., Li, H., & Hou, W. (2025). The analysis of strategic management decisions and corporate competitiveness based on artificial intelligence. Scientific Reports. https://doi.org/10.1038/s41598-025-02842-x

[6] Huynh, M. T., Gunkel, M., & Veglio, V. (2025). Nurturing a data-driven mindset for data-driven transformation: A conceptualization and research framework. Strategic Change, 1–13. https://doi.org/10.1002/jsc.2678

[7] Huynh, M. T. (2025). Individual data-driven mindset and decision-making performance: The mediating roles of effort and persistence. Information Systems Frontiers. https://doi.org/10.10796-025-10647-6

[8] Shahzad, K., Imran, F., & Butt, A. (2025). Digital transformation and changes in organizational structure: Empirical evidence from industrial organizations. Research-Technology Management, 68(3), 25–40. https://doi.org/10.1080/08956308.2465706

[9] Fernandes, A., & Frederick, D. (2025). Revolutionizing project management with artificial intelligence: Increasing efficiency and decision-making capabilities. Retrieved February 16, 2026, from https://acr-journal.com/article/revolutionizing-project-management-with-artificial-intelligence-increasing-efficiency-and-decision-making-capabilities-874/

[10] Ma, M., Wu, X., & Wang, X. (2025). A literature review of enterprises’ digital transformation based on the LDA topic model. Technology Analysis & Strategic Management. https://doi.org/10.1080/09537325.2578809

[11] Munce, S. (2024). Media review: The Sage Handbook of Mixed Methods Research Design. Journal of Mixed Methods Research, 18(4), 503–505. https://doi.org/10.1177/15586898241279880

[12] Dai, Z., & Jiang, Q. (2025). Climate policy uncertainty and corporate ESG performance: Evidence from Chinese listed companies. China Finance Review International, 15(3), 578.

[13] Zhao, X., Chen, Q., & Zhang, H. (2024). A study on the influencing factors of corporate digital transformation: Empirical evidence from Chinese listed companies. Scientific Reports, 14, 6243. https://doi.org/10.1038/s41598-024-56729-8

Downloads

Published

15-06-2026

Issue

Section

Articles

How to Cite

Chen, Z. (2026). The Impact of Data-Driven Management on Decision Consistency in Firms: Evidence from Chinese Manufacturing and Service Sectors. Frontiers in Business, Economics and Management, 23(3), 38-45. https://doi.org/10.54097/q63m2g11