Research Progress on the Effectiveness Evaluation of Digital Transformation in Manufacturing Enterprises

Authors

  • Chenming Zhang

DOI:

https://doi.org/10.54097/2zvg2651

Keywords:

Manufacturing, Digital Transformation, Effectiveness Evaluation, Transformation Paths

Abstract

Under the macro context of the Industry 4.0 wave and the "Made in China 2025" strategy, digital transformation has become an imperative path for the high-quality development of manufacturing enterprises. Focusing on the core issue of evaluating the effectiveness of digital transformation in manufacturing enterprises, this paper first elucidates the connotation and theoretical basis of digital transformation. Subsequently, it analyzes four major transformation paths: production digitalization, management digitalization, business model innovation, and organizational capability building. Based on this, a comprehensive effectiveness evaluation framework covering four dimensions—strategy, technology, organization, and benefit—is constructed. It is proposed that the effectiveness evaluation of digital transformation in manufacturing enterprises should adhere to systems thinking, emphasize the organic integration of process and results, and account for dynamic evolution characteristics. The findings of this study can provide a theoretical foundation and decision-making reference for manufacturing enterprises to implement effectiveness evaluation of digital transformation.

Downloads

Download data is not yet available.

References

[1] Development Research Center of the State Council. Development Report on Digital Transformation of China's Manufacturing Industry (2024) [R]. Beijing: Development Research Center of the State Council, 2024.

[2] China Electronics Standardization Institute. Maturity Model for Digital Transformation in Manufacturing Industry (2025 Edition) [S]. Beijing: China Electronics Standardization Institute, 2025.

[3] Mitra A, Singh P, Gupta R. Digital transformation in manufacturing: A systematic review and future directions [J]. Technological Forecasting and Social Change, 2024, 198: 122-138.

[4] Baiyere A, Salmela H, Tapanainen T, et al. Rethinking digital transformation: Beyond technology to organizational change [J]. Journal of Information Technology, 2025, 40(1): 56-72.

[5] Guanghua School of Management, Peking University. Report on Digital Intelligence Transformation of Chinese Enterprises (2024) [R]. Beijing: Peking University, 2024.

[6] Annarelli A, Battistella C, Nonino F, et al. Digital transformation strategies for manufacturing SMEs: A configurational approach [J]. Journal of Business Research, 2024, 155: 113-129.

[7] Qi Yudong, Xiao Xu, Cai Chengwei. Path selection and performance evaluation of digital transformation in manufacturing industry [J]. Management World, 2024, 40(3): 78-92.

[8] Fu Jianhua, Wang Huacheng. Financial digital intelligence and enterprise value creation [J]. Accounting Research, 2023, 44(5): 34-45.

[9] Kane G C, Palmer D, Phillips A N, et al. The digital transformation paradox: Why many companies fail to realize value[J]. MIT Sloan Management Review, 2024, 65(2): 22-31.

[10] Vial G, Gregory R W. Understanding digital transformation dynamics: A process perspective [J]. The Journal of Strategic Information Systems, 2024, 33(2): 101-118.

[11] Matt C, Hess T, Benlian A, et al. Digital transformation strategies in the post-pandemic era [J]. Business & Information Systems Engineering, 2024, 66(2): 189-204.

[12] Nguyen T H, Le X C, Pham T H, et al. Navigating digital transformation under competitive pressure [J]. Journal of Innovation & Knowledge, 2024, 9(3): 100-118.

[13] Henriette E, Feki M, Boughzala I, et al. Balancing strategy, organization, and technology in digital transformation [J]. Information Systems Management, 2025, 42(1): 78-94.

[14] Li Hui, Zhang Cheng. Underlying logic and implementation paths of digital transformation in manufacturing industry [J]. Economic Research Journal, 2024, 59(4): 112-126.

[15] Zhang Min, Wang Zhiqiang. Research on evaluation index system for enterprise digital transformation effectiveness [J]. Friends of Accounting, 2024(8): 65-72.

[16] Wang Jianguo, Liu Wei, Chen Ming. Construction of digital transformation evaluation model for intelligent manufacturing [J]. Science and Technology Management Research, 2024, 44(5): 98-106.

[17] Chen Chunhua, Zhu Li. Paths and mechanisms for reshaping organizational capabilities in the digital era [J]. Journal of Management Sciences in China, 2024, 27(2): 1-15.

[18] Liu Wei, Wang Jianguo. Typical paths and performance differences of digital transformation in manufacturing enterprises [J]. Science & Technology Progress and Policy, 2024, 41(8): 76-85.

[19] Ministry of Industry and Information Technology. Guidelines for Digital Transformation of SMEs (2025 Edition) [S]. Beijing: Ministry of Industry and Information Technology, 2025.

[20] Wu Xiaobo, Du Jian. Dynamic capability building and competitive advantage in the digital era [J]. Journal of Industrial Engineering and Engineering Management, 2024, 38(3): 1-14.

Downloads

Published

15-03-2026

Issue

Section

Articles

How to Cite

Zhang, C. (2026). Research Progress on the Effectiveness Evaluation of Digital Transformation in Manufacturing Enterprises. Frontiers in Business, Economics and Management, 22(3), 25-28. https://doi.org/10.54097/2zvg2651