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创造可持续的文化产业:人工智能和全球价值链的视角。

Creating Sustainable Cultural Industries: The Perspective of Artificial Intelligence and Global Value Chain.

机构信息

School of Economics and Management, Communication University of China, Beijing 100024, China.

出版信息

J Environ Public Health. 2022 Aug 22;2022:6768388. doi: 10.1155/2022/6768388. eCollection 2022.

DOI:10.1155/2022/6768388
PMID:36046080
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC9423948/
Abstract

In the era of artificial intelligence (AI), cultural industries have introduced new development opportunities, and their global value chain (GVC) position is receiving more attention. This study uses panel data from global cross-borders from 56 countries (regions) as the research sample to empirically analyze the impact of AI on improving the GVC position of cultural industries using the double fixed effects regression model and examines the heterogeneity effect. The results confirm that there is a significant positive correlation between AI and the GVC position of cultural industries. The mechanism test shows that AI impacts the division of labor position in the GVC of cultural industries mainly through technological innovation and the industrial structure. Heterogeneity analysis shows that AI has a significant effect on promoting the cultural industry's GVC position in high-income countries (regions) but it has no significant effect on low- and middle-income countries (regions). The results of this study can provide a useful reference for improving the division of labor positions in the GVC and better promoting the development of cultural industries.

摘要

在人工智能(AI)时代,文化产业带来了新的发展机遇,其全球价值链(GVC)地位受到了更多关注。本研究使用来自全球 56 个国家(地区)的跨境面板数据作为研究样本,采用双固定效应回归模型实证分析了 AI 对提高文化产业 GVC 地位的影响,并检验了异质性效应。结果证实,AI 与文化产业 GVC 地位之间存在显著的正相关关系。机制检验表明,AI 通过技术创新和产业结构影响文化产业 GVC 的分工地位。异质性分析表明,AI 对促进高收入国家(地区)文化产业 GVC 地位具有显著影响,但对中低收入国家(地区)没有显著影响。本研究结果可为提高文化产业 GVC 分工地位、更好地促进文化产业发展提供有益参考。

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本文引用的文献

1
Carbon Emission Calculation and Influencing Factor Analysis Based on Industrial Big Data in the "Double Carbon" Era.基于“双碳”时代工业大数据的碳排放计算与影响因素分析。
Comput Intell Neurosci. 2022 Feb 28;2022:2815940. doi: 10.1155/2022/2815940. eCollection 2022.
2
Machine behaviour.机器行为。
Nature. 2019 Apr;568(7753):477-486. doi: 10.1038/s41586-019-1138-y. Epub 2019 Apr 24.
3
Three laws of robotics and surgery.机器人学与外科学的三大定律。
J Endourol. 2008 Aug;22(8):1557-60. doi: 10.1089/end.2007.0106.