人工智能研究能力的趋同分析:欠发达国家是否正在追赶发达国家?

IF 1.7 4区 经济学 Q3 DEVELOPMENT STUDIES Journal of International Development Pub Date : 2024-04-06 DOI:10.1002/jid.3901
Saima Javed, Yu Rong, Babar Nawaz Abbasi
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引用次数: 0

摘要

本研究采用对数 t 收敛技术(LCT)和动态空间有序概率(DSOP)模型,探讨欠发达国家是否正在追赶发达国家。研究结果表明:首先,人工智能研究能力总体上没有趋同。其次,俱乐部聚类分析显示,五组国家中有四组在人工智能研究产出方面趋同,四组国家中有三组在人工智能专利授权方面趋同。第三,各国的人工智能研究能力正在经历一个缓慢的分化过程。第四,国家的地区、收入组别和群组影响着趋同进程。
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Convergence analysis of artificial intelligence research capacity: Are the less developed catching up with the developed ones?

This study examines whether less developed countries are catching up with developed ones using the log t convergence technique (LCT) and the dynamic spatial ordered probit (DSOP) model. The findings revealed that first, there is no overall convergence in AI research capacity. Second, club clustering analysis showed convergence in four of the five groups of countries on AI research output and in three of the four groups on AI patent grants. Third, the countries are experiencing a slow divergence process in AI research capacity. Fourth, the region, income group and cluster of the countries are influencing the convergence process.

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来源期刊
CiteScore
2.40
自引率
0.00%
发文量
109
期刊介绍: The Journal aims to publish the best research on international development issues in a form that is accessible to practitioners and policy-makers as well as to an academic audience. The main focus is on the social sciences - economics, politics, international relations, sociology and anthropology, as well as development studies - but we also welcome articles that blend the natural and social sciences in addressing the challenges for development. The Journal does not represent any particular school, analytical technique or methodological approach, but aims to publish high quality contributions to ideas, frameworks, policy and practice, including in transitional countries and underdeveloped areas of the Global North as well as the Global South.
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