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基于PMC指数模型的我国省级"人工智能+"政策量化评价研究

李胜会 姜逸轲 顾东明

工业技术经济2025,Vol.44Issue(10):117-127,11.
工业技术经济2025,Vol.44Issue(10):117-127,11.DOI:10.3969/j.issn.1004-910X.2025.10.012

基于PMC指数模型的我国省级"人工智能+"政策量化评价研究

Quantitative Evaluation Research on Provincial"Artificial Intelligence+"Policies in China Based on PMC Index Model

李胜会 1姜逸轲 1顾东明1

作者信息

  • 1. 华南理工大学公共管理学院,广州 510641
  • 折叠

摘要

Abstract

Under the background of the new round of global scientific and technological revolution and the accelerated evolu-tion of industrial transformation,"artificial intelligence+",as a practical paradigm of integration and innovation,is promoting sys-tematic changes in various fields of society by means of technological empowerment.This paper takes China's provincial policies of"artificial intelligence+"as the research object,analyzes 38 policies of"artificial intelligence+"in China with the help of word frequency analysis and semantic network analysis,and builds a PMC index evaluation model of China's provincial policies of"artifi-cial intelligence+"on this basis.After evaluating the selected 16 provincial policies,it is found that the average PMC index score of the 16 provincial policies is 7.38,of which Zhejiang Province has the highest policy score(8.83)and Shaanxi Province has the lowest policy score(5.62).It is found that the overall score of"artificial intelligence+"policies at the provincial level in China is good and there are no bad policies,but there are significant differences between the policies in the eastern,central and western re-gions.In addition,most policies still have much room for improvement in terms of policy timeliness,empowerment direction and policy tools.In this regard,we can improve it from the aspects of enriching policy subjects,expanding application direction,per-fecting policy tools and optimizing policy timeliness.

关键词

人工智能+/融合创新/政策文本分析/PMC指数模型/政策时效/政策工具/协同治理/政策优化

Key words

artificial intelligence+/integration and innovation/policy text analysis/PMC exponential model/policy opti-mization/policy validity period/policy tools/collaborative governance

分类

管理科学

引用本文复制引用

李胜会,姜逸轲,顾东明..基于PMC指数模型的我国省级"人工智能+"政策量化评价研究[J].工业技术经济,2025,44(10):117-127,11.

基金项目

国家社会科学基金资助重点项目"急性冲击与慢性压力叠加下产业链韧性提升的机制与政策研究"(项目编号:21AGL027). (项目编号:21AGL027)

工业技术经济

OA北大核心

1004-910X

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