Fig 1.
Research framework of the PMC index model for the quantitative evaluation of China’s artificial intelligence policies.
Fig 2.
Construction process of the PMC index model for China’s artificial intelligence policies.
Table 1.
Selected sample of China’s artificial intelligence policy documents.
Fig 3.
Trend of the number of artificial intelligence policy documents issued by the Chinese central government (2016–2025).
Note: The dashed line indicates the overall trend in annual policy issuance.
Fig 4.
Top 20 high-frequency terms in China’s artificial intelligence policy documents.
Fig 5.
Semantic co-occurrence network of high-frequency terms in China’s artificial intelligence policy documents.
Table 2.
Quantitative evaluation indicator system and sources for China’s artificial intelligence policiesprimary variable.
Table 3.
Multi-input–output table of PMC model variables for China’s artificial intelligence policies.
Table 4.
PMC index–based policy classification standards.
Table 5.
Selected AI policy samples in China.
Table 6.
Multi-input–output table for the five selected AI policies in China.
Table 7.
PMC index of the five selected AI Policies in China.
Table 8.
PMC matrices of the five selected AI policies in China.
Fig 6.
PMC surface of policy P1.
Fig 7.
PMC surface of policy P2.
Fig 8.
PMC surface of policy P3.
Fig 9.
PMC surface of policy P4.
Fig 10.
PMC surface of policy P5.
Fig 11.
Radar chart of China’s artificial intelligence policies.
Fig 12.
Distribution of nine primary indicators across five representative Chinese artificial intelligence policies.
(Note: The black dots in the figure represent outliers in each data group.).