•  
  •  
 

Bulletin of Chinese Academy of Sciences (Chinese Version)

Keywords

digital-intelligent transformation, green transformation, global trends, international experience

Abstract

The coordinated digital-intelligent and green transformation of manufacturing is emerging as a major direction for advancing the transformation and upgrading of the global manufacturing sector and reshaping industrial competitive advantages. This study systematically analyzes the evolution of this transformation worldwide, the transformation pathways adopted by different economies, and the strategic priorities of key industries. It then examines Germany, the United States, and Japan as representative cases to illustrate their respective approaches and practices. Drawing on China’s existing development foundations and current shortcomings, the study puts forward corresponding policy recommendations. The findings reveal that the global coordinated transformation has progressively moved from parallel evolution to a stage of deep integration, with different economies following diversified and multi‑tiered transition paths. In key manufacturing sectors—including new energy equipment, high‑end equipment, and traditional energy‑intensive industries—the global landscape exhibits feature of intensified agglomeration and regional reconfiguration. By synthesizing the practical experiences of Germany, the U.S., and Japan, the study argues that China urgently needs to strengthen strategic coordination and pursue breakthroughs in key technologies, improve industrial data governance and green standards systems, adopt differentiated and tiered implementation strategies, and deepen international cooperation and participation in global rule-making. And these measures are designated to promote deeper integration between the digital-intelligent and green transformation of China’s manufacturing sector, thereby enhancing industrial-chain resilience and international competitiveness.

First page

1574

Last Page

1584

Language

Chinese

Publisher

Bulletin of Chinese Academy of Sciences

References

[1] 习近平. 做强做优做大实体经济. 求是, 2026, (10): 4-9. Xi J P. Strengthening, optimizing and expanding the real economy. Qiushi, 2026, (10): 4-9. (in Chinese)

[2] 宋大伟. 科技战略咨询研究肩负国家使命. 中国科学院院刊, 2016, 31(8): 857-869. Song D W. Science and technology strategy consulting research bears national mission. Bulletin of Chinese Academy of Sciences, 2016, 31(8): 857-869. (in Chinese)

[3] 王云平, 蒋安玲. "双碳"目标下加快推进我国绿色制造体系构建——基于市场化体系构建的角度. 重庆邮电大学学报(社会科学版), 2024, 36(6): 127-138. Wang Y P, Jiang A L. Accelerating the construction of China's green manufacturing system under the goals of "emission peak and carbon neutrality": From the perspective of constructing a market-oriented system. Journal of Chongqing University of Posts and Telecommunications (Social Science Edition), 2024, 36(6): 127-138. (in Chinese)

[4] 黄烨菁, 李锦明. 制造业数智化、产业规模和全球价值链地位——以发展中国家为对象的研究. 上海大学学报(社会科学版), 2026, 43(1): 114-135. Huang Y J, Li J M. Manufacturing digital intelligence, industrial scale, and global value chain position—A study on developing countries. Journal of Shanghai University (Social Sciences Edition), 2026, 43(1): 114-135. (in Chinese)

[5] 王梦颖, 张诚. 数字基础设施建设与发展中国家绿色产品出口. 世界经济研究, 2023, (3): 17-30. Wang M Y, Zhang C. Digital infrastructure construction and green product export of developing countries. World Economy Studies, 2023, (3): 17-30. (in Chinese)

[6] 孔晓瑞, 周静, 李凯. 数字化转型赋能制造业绿色低碳发展的机理与效应研究. 软科学, 2025, 39(10): 68-75. Kong X R, Zhou J, Li K. Mechanism and effects of digital transformation in empowering the green and low-carbon development of the manufacturing industry. Soft Science, 2025, 39(10): 68-75. (in Chinese)

[7] 杨丹辉. 全球产业链重构的趋势与关键影响因素. 人民论坛·学术前沿, 2022, (7): 32-40. Yang D H. Trends and key influencing factors of global industrial chain restructuring. People's Tribune·Academic Frontiers, 2022, (7): 32-40. (in Chinese)

[8] 顾佰和, 王宏乾, 孙玉玲, 等. 主要发达经济体绿色低碳技术创新政策实践、经验及启示. 中国科学院院刊, 2026, 41(2): 342-351. Gu B H, Wang H Q, Sun Y L, et al. Practices, experiences, and insights from major developed economies on green and low-carbon technology innovation policies. Bulletin of Chinese Academy of Sciences, 2026, 41(2): 342-351. (in Chinese)

[9] 孟凡生, 于建雅. 新能源装备智造发展影响因素作用机理研究. 科研管理, 2019, 40(5): 57-70. Meng F S, Yu J Y. A study of the mechanism of action for the influence factors on development of intelligent manufacturing of new energy equipment. Science Research Management, 2019, 40(5): 57-70. (in Chinese)

[10] 穆荣平, 郭京京, 李雨晨, 等. "十五五"先进制造业集群创新发展态势、问题和建议. 中国科学院院刊, 2026, 41(7): 1329-1342. Mu R P, Guo J J, Li Y C, et al. Innovation-driven development of advanced manufacturing industry clusters: Trends, issues, and implications for 15th Five-Year Plan. Bulletin of Chinese Academy of Sciences, 2026, 41(7): 1329-1342. (in Chinese)

[11] 张玺, 宋洁, 侍乐媛, 等. 新一代信息技术环境下的高端装备数字化制造协同. 管理世界, 2023, 39(1): 190-203. Zhang X, Song J, Shi L Y, et al. Collaboration for digital manufacturing of high-end equipment in the era of new-generation information technology environment. Journal of Management World, 2023, 39(1): 190-203. (in Chinese)

[12] 刘汉初, 樊杰, 周道静, 等. 2000年以来中国高耗能产业的空间格局演化及其成因. 经济地理, 2019, 39(5): 110-118. Liu H C, Fan J, Zhou D J, et al. The evolution of spatial distribution and its influencing factors of high-energy intensive industry in China since 2000. Economic Geography, 2019, 39(5): 110-118. (in Chinese)

[13] 贺德方, 陈涛, 刘辉, 等. 科技创新与产业创新深度融合的政策实践与对策分析. 中国科学院院刊, 2025, 40(5): 781-794. He D F, Chen T, Liu H, et al. Policy practices and countermeasures analysis on the deep integration of technological innovation and industrial innovation. Bulletin of Chinese Academy of Sciences, 2025, 40(5): 781-794. (in Chinese)

Share

COinS